List of PhD projects for 2018
Additional list of PhD projects (10.-30.09.2018)
Supervisor: Dominique Unruh
Digital communication permeates all areas of today’s daily life. Cryptographic protocols are used to secure that communication. Quantum communication and the advent of quantum computers both threaten existing cryptographic solutions, and create new opportunities for secure protocols. The security of cryptographic systems is normally ensured by mathematical proofs. Due to human error, however, these proofs often contain errors, limiting the usefulness of said proofs. This is especially true in the case of quantum protocols since human intuition is well-adapted to the classical world, but not to quantum mechanics. To resolve this problem, we need methods for verifying cryptographic security proofs using computers (i.e., for “certifying” the security). This is the goal of the ERC Consolidator Grant project CerQuS.
Within the scope of this project, we need to formalize quantum mechanics in a proof assistant and come up with suitable reasoning methods and tools within it. This phd project will develop such foundations in the proof assistant Isabelle/HOL (targeting WP2 of the ERC project).
The PhD project’s outcomes will be an integral part of our research towards the verification of quantum cryptography, and towards ensuring highest trust in future generations of cryptographic systems, even after the arrival of quantum computers.
Institute of Computer Science, J. Liivi 2, 50409, Tartu, Estonia
Phone: (+372) 737 5445, e-mail: ics [ät] ut.ee, web: www.cs.ut.ee
Supervisor: Fabrizio Maria Maggi
Predictive business process monitoring aims at predicting the outcome of ongoing cases of a business process based on past execution traces. A wide range of techniques for this predictive task have been proposed in the literature. However, the interpretability of these methods is very limited. This means that when a prediction is given it is hard to understand the reasons why the method returned the prediction of a certain outcome and not of another. The goal of this doctoral project is to propose a set of techniques for predictive process monitoring that are easy to explain so that also non-technical users can be provided with insights of the logic behind the predictive model employed.
Supervisor: Meelis Kull
Complex intelligent systems, such as self-driving cars and medical expert systems, rely on classifiers built using machine learning. For example, a self-driving car might use a multi-class classifier to decide whether ahead there is a human (class 1), other obstacle (class 2), or clear road (class 3). It is often required that these classifiers output confidence together with their predictions, as this allows picking safer options whenever the confidence becomes too low. Therefore, it is extremely important for the classifier not to be overly confident, as this would increase the risk of very costly errors. Over-confidence results from a failure to account for all uncertainty about the context where the classifier is applied.
The goal of this PhD project is to develop methods which learn to accurately account for uncertainty when learning deep neural networks. First steps towards this goal have been recently published [1,2]. In  deep neural net classifiers have been demonstrated to be over-confident and to require a post-hoc procedure to achieve better calibrated confidence estimates. In  deep net regression models have also been shown to require calibration. The approach taken in  is a simple single parameter method called temperature scaling, which can be viewed as retraining an additional simple layer on top of the existing layers of the deep neural net. In an ongoing work (to be submitted in January 2019 for publication) we are proposing to use a more complicated fully connected layer instead, and demonstrate that this Dirichlet layer as we call it results in even better calibrated probabilities. We are also showing that the new method is a generalization of temperature scaling  and our own earlier proposed beta calibration [3,4]. We envision that a similar approach could be developed for regression.
Supervisor: Amnir Hadachi
Simultaneous Localization and Mapping (SLAM) in self-driving cars is the problem of reconstructing or updating a map of an environment while simultaneously tracking the location of the vehicle within it. Over the last decade, different sensors have been used to perform this task, like cameras, lidars, and radars by extracting different types of features based on the input data. Lately, due to the increasing computational power and more efficient algorithms, the research has moved to abandon feature extraction and rely on the raw output of the sensors. Most of these approaches have been tested on static and/or indoor environments leaving their performance in dynamic outdoor environments to be below desirable. This thesis aims to investigate the problem of fusing potentially conflicting information coming from an array of heterogeneous sensors in order to localize the vehicle and estimate the configuration of the surrounding in a non-static environment. It will propose a three-way multisensory fusion of camera, lidar and radar data to be used by a Direct-SLAM approach in a dynamic environment.
Supervisor: Jaak Vilo
Increasingly there is need to reuse the Real World Data for health, disease, treatments and evidence/outcomes information. The EHDEN network is building an ecosystem and information processing layers to utilise health data from many countries and healthcare providers that would total around 400M individuals globally and 100M in Europe. Based on OMOP Common Data Model (CDM) these data can be compared in distributed manner. No data source seeks to reveal all individual patient level information, yet there is need to perform aggregate queries and run machine learning applications trained on one data source on all the others. In the current PhD proposal we will develop machine learning methods and applications that can firstly be used to predict outcomes based on prior evidence; reveal most interesting features in the data (feature extraction), develop explainable models behind the data, and develop cross-database validations of trained models.
Supervisor: Leopold Parts
The diagnostic standard for a large number of illnesses is an expert looking at an image, and performing a classification task based on their years of accumulated experience. The acquisition is digitized and automated, which has led to a high volume of data. As a result, deep catalogs of annotated medical images have been generated at large centers, and could now be used to improve standard of care.
The expected outcomes of this project are computational models that enhance medical images by improving their quality, and annotating their contents. We will rely on data banks available at our industrial collaborator PerkinElmer, and academic collaborators at the Sanger Institute to learn a model of high-resolution tissue images that is able to "restore" a lower resolution scan to a better quality, thus providing better data from fixed instrumentation. We will similarly make use of the large accumulated data banks to learn models that are able to classify images according to expert annotations, and to highlight the reasons for these annotations in the image.
Supervisor: Satish Narayana Srirama
Serverless computing is a recent trend in cloud computing with the potential to radically evolve the software technology landscape. The paradigm is proposing to entirely bypass user involvement in managing cloud resources. The popularity is attributed to the ability to virtualize the internal logic of a cloud native application, so that individual function calls are served remotely from the cloud and thus can harness function-level auto-scaling.
That is, with FaaS (Function-as-a-service) applications can add capacity only to the portion of the code that consumes it, simplifying scaling and achieving cost savings compared to VMs. Transparent and fine-grained scaling is particularly efficient for event-centric systems, such as in the Internet of Things (IoT), where actions need to rapidly kick-in to respond to events generated by software, data, business processes, or the physical world. In IoT application setups, the serverless platforms can be deployed across the Fog topology that is established across the device hierarchy involving routers, switches, gateways etc., till the cloud. Fog computing pushes the idea of processing the sensor data closer to the source instead of the cloud, to reduce latency.
The proposed thesis is directly related to the research being performed by the group in the cloud computing and IoT domains, where the group is very active and has made significant contributions in the past few years. Recently the group got funding for EU H2020 RADON project. The project should provide the student access to the respective infrastructure and the most recent and interesting research challenges both from academia and industry. This should be motivating the student to finish his thesis in stipulated time.
Supervisor: Mark Fišel
Neural machine translation can work for language pairs for which there is no direct training data available, due to the zero-shot effect. The aim of this PhD project is to explore monolingual neural translation (for example from Estonian to Estonian) and its applications to grammatical error correction, style transfer and text simplification. Requirements to successful candidates: strong background in language processing methods and neural network applications.
Supervisor: Kaur Alasoo
Genome-wide associations studies have identified thousands of genetic variants associated with complex traits and diseases. However, a key challenge remaining is translating these associations to actionable molecular mechanisms that can be used to develop novel strategies for disease treatment and prevention. A popular approach is to use large-scale gene expression profiling to
identify genes whose activity levels (‘expression’) are associated with disease variants. While significant resources have been invested into collecting such terabyte-scale datasets across human tissues, cell types and cellular context, they are scattered across many independent studies and repositories. Consequently, performing even simple queries such as “which genes are regulated by the disease variant and which cell types are important?” is currently impossible. The first aim of this PhD project is to develop a robust and portable data analysis pipeline that will enable us to compile the largest catalogue of genetic variants associated with gene expression across tissues, cell types and cellular contexts. The second aim of the project is to use the catalogue to discover latent (hidden) biological process in the dataset the influence the expression of a large number of genes across cell types and conditions. Finally, the student will use several machine learning and statistical techniques to characterise the molecular mechanisms underlying the discovered biological processes and how they contribute to the development of complex traits and diseases.
Supervisor: Alexander Udo Nolte
Time-bounded events such hackathons, data dives, codefests, hack-days, sprints or edit-a-thons have become a global phenomenon with a plethora of events happening across the globe every week. They have been particularly embraced by the start-up community because they come with the promise of fostering innovation and serving as a breeding ground for young entrepreneurs.
However, while the Estonian economy in particular promotes an entrepreneurial culture specifically in the IT sector there is little to no research on how hackathon sustainability let alone on how hackathons have to be designed in order for them to contribute to existing entrepreneurial practices. Drawing from qualitative and quantitative data sources this project aims at closing this gap by developing a comprehensive framework of interdependent factors that promote hackathon sustainability thus extending entrepreneurial theory. Using this framework as a basis the candidate will employ an action research methodology to iteratively develop, refine
and evaluate a socio-technical approach that fosters the transition from hackathon projects to fruitful start-up companies thus contributing to entrepreneurial practice as well.
Supervisor(s): Raimundas Matulevičius, Alexander Nolte
The internet of things (IoT) has produced an integration of a vast network of sensors and objects, exchanging data within devices and the internet. With its expected exponential growth over time, incentives for malicious parties increase as well. The threats posed by implementing IoT is multifaceted, encompassing people, process, objects, and data, growing in number and complexity.
This research study contributes a systematic approach to continuous research, innovation, evaluation, and training in IoT systems security, covering assets, security risks, and their countermeasures, by utilizing hackathons. It proffers, through goal-oriented hackathons, a series of activities and goals that bring together professionals and domain experts over short periods to apply knowledge in tackling specific problems in IoT security. This research aims to support stakeholders in maintaining a sustainable high level of security, providing security countermeasures to mitigate the evolving security risks in IoT systems.
Supervisor: Tomi Koivisto
Osakestefüüsika lagranžiaanid on invariantsed globaalsetel Lorentzi teisendustel ning gravitatsiooni arvestades dünaamilises aegruumis ka lokaalsetel Lorentzi teisendustel. Nagu juhendaja oma kaastöölistega on hiljuti näidanud, on osakestefüüsika elektronõrga kalbratsioonisümmeetria rikkumise Higgsi mehhanismile analoogiline skeem võimalik ka Lorentzi sümmeetria spontaanseks rikkumiseks, kusjuures aegruumi geomeetriat kirjeldav meetrika ilmub siis alles sümmeetria rikutud faasis. Selline lähenemine seab gravitatsiooni osakesefüüsika teooriatega sarnastele alustele, algse teooria koostisosadeks on vaid kalibratsiooniväli ja Higgsi väljale sarnane väli. Viimast võiks nimetada Cartani kroononiks, kuivõrd see määrab aja suuna Cartani geomeetrias. Doktoriprojektis arendatakse teooria Cartani geomeetrilist ja algebrodünaamilist formulatsiooni edasi ja uuritakse vastavaid järeldusi.
Doktorant hakkab tööle tihedas koostöös juhendajaga vastava uurimisprogrammi elluviimisel. Esimeses etapis on doktorandi ülesandeks tutvuda Cartani geomeetriaga ja mõista selle omadusi komplekssel juhul. Seejärel on kavas koostada gravito-elektronõrk teooria, kus Lorentzi seostuse anti-eneseduaalne osa kirjeldaks nõrka interaktsiooni ning Lorentzi sümmeetria Weyli laiendus hõlmaks U(1) ja mastaabi sümmeetriaid. Eesmärk on ühendada Cartani kroonon ja Higgsi väli kasutades sümmeetriarühmade seost SO(4,C)=SU(2,C)xSU(2,C). Projekti viimase faasi sisu on rakendada teooriat kosmoloogiale, kus Cartani kroonon teadaolevalt ennustab tumeainet kui puhtalt geomeetrilist efekti. On väga huvitav püüda siduda omavahel aja, meetrika, Plancki skaala ja elektronõrga sümmeetria rikkumine vaadates Higgsi inflatsiooni selles ühendatud raamistikus.
Institute of Physics, W. Ostwaldi tn 1, 50411, Tartu, Estonia. Web: www.fi.ut.ee
Supervisor: Carlos Perez Carmona
Approaches based on the functional traits of organisms can be very useful if we want to understand and predict the effects of global change on the assembly and functioning of biological communities. However, despite the importance of trait differences between members of the same species, most approaches have ignored intraspecific variability in trait values. In this project, we will explicitly consider intraspecific variability to try to improve our knowledge about 1) the role of functional redundancy, 2) the responses of species and ecosystem functioning to climate change, and 3) the relationship between environment and the composition and structure of plant communities. The project will combine experimental approaches with the development of novel analytical techniques, with the ultimate goal of improving our understanding of the processes that shape biodiversity at local and global scales
Institute of Ecology and Earth Sciences, Vanemuise 46, 51014, Tartu, Estonia. Phone: (+372) 737 5835, e-mail: om [ät] ut.ee, web: www.omi.ut.ee
Supervisor: Maarja Öpik
Taimejuurtega sümbioosis elavad krohmseened moodustavad arbuskulaarset mükoriisat (AM), ning on looduslike ning inimmõjuliste ökosüsteemide olulised liikmed. Krohmseente elurikkuse uuringud on viimastel aastatel näidanud selgeid mustreid globaalsel skaalal, sh madalat globaalset endeemsust ning kõrget elurikkust troopilistes piirkondades. Troopilise elurikkuse tulipunktina on Sri Lanka hea mudelsüsteem, kus uurida inimese poolt põhjustatud ning looduslike stressorite mõju krohmseente elurikkusele ning nende vastustele muutuvatele keskkonnatingimustele.
Antud doktoriprojekti eesmärgiks on uurida AM seenekoosluste mitmekesisusemustreid erineva maakasutuse ning keskkonnastressorite tingimustes Sri Lanka ökosüsteemides. Kirjeldatakse krohmseente elurikkuse jaotumiste peamistes ökosüsteemides ning testitakse katseliselt, kuidas vastavate ökosüsteemide krohmseened taluvad inimtekkelist stressi (nt mulla mehhaaniline häiring, herbitsiidid, pestitsiidid) ning keskkonnastressi (põud, üleujutused).
Doktoriprojekti tulemused on olulised inimese suureneva surve tõttu looduslikele ökosüsteemidele, mille tagajärjel looduslike elupaikade pindala väheneb ning killustub. Samuti annab antud projekt teadmisi, et paremini kujundada strateegiaid elupaikade säästlikuks majandamiseks mullaelustiku abil ja mullaelustikku arvesse võttes, ökosüsteemide taastamiseks ning keskkonnamuutustega kohanemiseks nii piirkondlikus kui globaalses skaalas.
Supervisors: Riinu Rannap ja Leho Tedersoo
Batrachochytrium dendrobatidis (Bd) on väga nakkav patogeenne seen, mis põhjustab kahepaiksetel kütridiomükoosi ehk keratiniseerunud nahakudesid hävitavat haigust. Kütridiomükoos vähendab kahepaiksete arvukust kogu maailmas ning on kaasa toonud ka liikide väljasuremisi. Euroopas on kütridiomükoos põhjustanud paljude kahepaiksepopulatsioonide väljasuremist Hollandis ja Hispaanias. Kuigi tegemist on kahepaiksetel surma põhjustava haigusega, leidub siiski mitmetes Euroopa riikides Bd-nakkusega populatsioone, kus haiguspuhanguid pole täheldatud. Senini pole haiguspuhangute esinemise ja kahepaiksete elupaiga kvaliteedi omavahelisi (nt loomade stressitaseme kaudu avalduvaid) seoseid uuritud. Antud doktoriprojekt uurib Bd levikut Eestis, mille käigus märgitakse Eesti ära ka ülemaailmses „Globaalne Bd kaardistamine“ projektis. Tuginedes meie esialgsetele uuringutele teame, et Bd’ga on nakatunud mitmed Eesti kahepaiksete populatsioonid, sealhulgas vähemalt üks kõre ehk juttselg-kärnkonna (Bufo calamita) asurkond. Kõre kuulub Eestis I kaitsekategooria liikide hulka ning on kantud rangelt kaitstava liigina ka Euroopa Liidu loodusdirektiivi IV lisasse. Varasemates uuringutes on selgunud, et kärnkonnalised on kütridiomükoosile eriti vastuvõtlikud. Antud töös uuritakse Bd’ga nakatumise mõju selle ohustatud kärnkonnaliigi populatsiooni elujõulisusele (sh sigimiskäitumisele, suremusele). Kõrede asurkonnad Eestis asuvad leviala põhjapiiril, on väikesearvulised ja killustunud, mistõttu on oluline välja selgitada elupaiga kvaliteedi mõju kütridiomükoosi avaldumisele. Kui selgub, et haiguse avaldumine on seotud elupaiga kvaliteediga, on võimalik elupaiga tingimusi parandades ära hoida kahepaiksete massilist suremust.
Institute of Ecology and Earth Sciences, Vanemuise 46, 51014, Tartu, Estonia. Phone: (+372) 737 5835, e-mail: om [ät] ut.ee, web: www.omi.ut.ee
Institute of Computer Science, J. Liivi 2, 50409, Tartu, Estonia. Phone: (+372) 737 5445, e-mail: ics [ät] ut.ee, web: www.cs.ut.ee
Supervisors: Marlon Dumas, Luciano Garcia-Banuelos, Peeter Laud
Existing process mining methods are not privacy-aware, yet they deal with private customer data. The aim of this project is to develop methods for process mining with provable privacy guarantees. The project will adapt existing privacy-preserving data processing methods in order to implement common process mining operations, such as automated process discovery, conformance checking and log delta analysis. The challenge will be how to provide suitable privacy guarantees in this context, in a scalable manner and while minimizing the loss of accuracy (and hence utility) due to noisification of output data.
Supervisors: Ahmed Awad, Sherif Sakr
The goal of this doctoral project is to develop a comprehensive library to handle uncertainty in data streams. One challenge is to build a comprehensive taxonomy of uncertainty causes and find or develop techniques to handle such causes. Another challenge is to build the library in a portable manner that allows invoking the uncertainty handling techniques seamlessly at any stage of the data processing pipeline from the source to sink.
Supervisors: Meelis Kull
There are two key ingredients that have made deep neural networks outperform other machine learning methods across many domains. One of these ingredients is structure: deep hierarchical nested functions can represent real-life dependencies better (that is with fewer parameters) than shallow functions. The other key ingredient is differentiable objective function – instead of having to perform a blind search in the parameter space, the training of deep neural networks is guided by the gradient, pointing towards better values of parameter values. The mini-revolutions within deep learning have mostly been achieved by radically changing one of the above key ingredients. Introduction of convolutional structure, dropout and batch normalisation are examples of successful modifications of structure. There are far fewer examples of successful changes of the objective function. Classification algorithms have mostly been trained with cross-entropy all along. Important achievements were introduction of reconstruction loss resulting in the auto-encoder networks, and the follow-up introduction of generative adversarial networks which combine the generative and discriminative objectives.
The goal of this PhD project is to develop new objective functions for deep learning. The main shortcoming of training classifiers with current objective functions such as cross-entropy is that the network only learns the features that best discriminate between the classes in the training data. This makes the network very vulnerable to adversarial examples and more generally, the network predicts poorly whenever applied in a context which is even slightly different from the training context. For example, in object recognition from images many modern networks rely mostly on features about texture, and perform extremely poorly if texture is removed. While it is possible to shift the balance towards using more shape features, it remains fundamentally hard with current objective functions to encourage the network to learn many different kinds of features simultaneously, such as colour, texture, shape and position of both the whole object and its parts, as well as the surrounding objects and background. Only learning all these features can make the network so robust that it recognises the object even if many of these features are not available.
Supervisors: Dietmar Pfahl
System-level testing has become a highly automated practice in software industry. Growing size and configurability of software, which needs to be tested in ever-shorter cycles, has resulted in high demand for optimizing test suites with regards to efficiency and effectiveness. With the help of machine learning, three approaches with prototypical tool support will be developed for test suite optimization. The approaches provide (i) a method to develop a model that predicts in a mutation testing context which mutants won’t be killed, thus informing about missing tests in the test suite, (ii) a method to support semi-automatic test oracle generation, thus completing automatically generated test data, and (iii) a method to detect usage profile differences between test execution logs and end user execution logs, thus informing about gaps in the test suite. The three approaches will be integrated and evaluated in case studies with industry.
Estonian Marine Institute, Mäealuse 14, 12618, Tallinn, Estonia. Phone: (+372) 671 8902, fax: (+372) 671 8900, web: www.sea.ee
Supervisors: Tuul Sepp (OM), Lauri Saks
All multicellular organisms have developed mechanisms to supress malignant processes. Our knowledge of these natural defence mechanisms against cancer is so far limited. A better understanding of adaptations to avoid cancer is crucial for building our understanding of evolution of cancer and finding novel possibilities for the treatment of cancer. Human activities have resulted in large-scale environmental modifications. This unintentionally creates possibilities for using polluted environments as “natural laboratories” for studying the evolution of cancer defence mechanisms. While it is known that organisms that are naturally exposed to environmental pollutants can evolve specific adaptations to cope with pollutants and their adverse effects on fitness, almost no attention has been focused on contemporary natural adaptations to environmental oncogenic factors. We will target Baltic Sea as one of the most polluted marine areas in the world, and study a gradient of more and less polluted habitats using flounders (Platichthys flesus) as model species. Previous studies have indicated that cancerous lesions are common in flounders. We predict that in polluted habitats, local adaptations have developed in flounders to overcome the negative physiological effects of environmental oncogenic factors. We plan to apply common garden approach to study contemporary evolution, and also develop cell lines to study the effects of specific oncogenic factors on cellular defence mechanism.
Supervisors: Georg Martin, Chris Hepburn (Otago Ü)
The current project plans to investigate energy movement in the form of primary production and dissolved organic carbon (DOC) within the shallow, near coastal ecosystem of the Baltic Sea. A large portion of the relevant literature cites macroalgae derived DOC as an important energy source for coastal marine communities worldwide.
DOC production rates of Baltic macroalgae species will be determined at a range of environmental conditions (e.g. light, nutrient concentration, salinity) and the physiological mechanisms underpinning DOC release will be explored. Understanding of why macroalgae release fixed carbon, a seemingly wasteful process, will be a key part of this study. Quantifying delivery of DOC released by macroalgae into the microbial loop will provide information on a key linkage in the marine food web in the Baltic. The productivity of heterotrophic bacteria on macroalgal surfaces (biofilms) and in the surrounding water will be determined. Existing long term quantitative macroalgae biomass and distribution data will be used to describe the status in the past (up to 1980s), present and future status under different climate change scenarios. This information can be used to highlight how macroalgae contribute to the food webs and implicate how changes to these communities through different disturbances as climate change, invasive species, eutrophication etc. would change it.
Institute of Physics, W. Ostwaldi tn 1, 50411, Tartu, Estonia. Web: www.fi.ut.ee
Supervisors: Lauri Aarik, Väino Sammelselg, Priidu Peetsalu
For the quality of safety devices, e.g., safety belt devices for cars/busses/airplanes are stated very rigid demands. Thereby, the details that fall under most significant stress after engage of the safety device must successfully pass through the tensile tests with a high over tensions and also work with periodic high tensions without breaking for long physical life. It is clear that the details like these as well full devices are projected already with high enough factor of safety, and during the production, both the details and full devices are controlled and tested carefully. Nevertheless, there could be structural defects already in raw materials or some impurity elements, which could be added into the samples during their production. These defects/impurities could not be detected during the production control or spot check but could influence the quality of the equipment during their exploitation. This doctoral study will deal, first, with the study of hidden defects and possible impurity elements in the safety device critical details using modern methods of solid sample characterization and study, and with bettering technology to avoid the critical defects and generation of the impurity elements, and at the same time not to higher manufacturing cost appreciably. Second, during the study will be controlled and developed the corrosion protective coatings of the metal parts of the devices so they can serve in corrosive environments longer time having a careful look at the same time.
Supervisors: Jaan Aarik, Aile Tamm, Kaupo Kukli
Resistive switching phenomena in different dielectric multilayers will be investigated during the doctoral studies. The goal of the studies is to seek and find multistate structures most suited to the possible applications in computer memories to store and elaborate data and information. During the PhD studies structure with optimized parameters will be selected, in order to thoroughly explore electrical properties of the multilayer stacks and examine the performance of memory cells. Design of memory matrices with high packing density will be aimed at, when selecting new materials for this purpose.
Supervisors: Velle Toll, Piia Post
Atmospheric aerosols, tiny solid and liquid particles suspended in the air, affect the climate through direct interaction with radiation and through modulation of cloud properties. Through these effects, anthropogenic aerosols mask poorly quantified fraction of greenhouse gas radiative forcing. These uncertain aerosol impacts on clouds make it difficult to assess how hot the future climate will be. To reduce the uncertainty in the aerosol forcing of Earth’s climate, improved observational constraints on cloud responses to aerosols will be derived using dedicated satellite observations of clouds at industrial pollution hot spots. Use of pollution hot spots helps to objectively identify the polluted and unpolluted properties of the clouds. This research is focused on aerosol-induced changes in cloud water, cloud thickness, cloud horizontal coverage and occurrence of rain. Although polluted clouds over ocean have been previously analysed, this project addresses knowledge gap in cloud responses over continents. Clouds polluted by aerosols detected from local to continental scales will be studied using wide range of satellite instruments. Various methods at various levels of complexity will be applied to detect polluted clouds in satellite images. In addition, temporal anomalies in cloud properties induced by closing or opening large factories and abrupt changes in aerosol emissions will be studied. The project results will help to reduce uncertainty in anthropogenic climate forcing and increase the reliability of the projections of future climate.
Supervisors: Heli Lukner, Andreas Valdmann, Peeter Saari
Computational imaging is a rapidly developing field in optics that is empowered by the availiability of sufficient computational capabilities. Conversly to classical imaging technologies where an image is captured directly onto a camera sensor, in computational imaging the data gathered is not the direct representation of the captured scene and a comprehensive image can be acquired only after post-processing the measured data. Interestingly, this could yield the benefit of severely reducing the complexity of the imaging device’s optical system or collecting information from the scene previously unattainable by conventional imaging methods. For example, it is possible to select the focus of an image during the post-processing.
One of the methods for computational imaging is single-pixel imaging where an object is illuminated with different light patterns and the intensity of the light reflected off of it is measured with a single-pixel detector. Measured intensity signals are paired with their respective patterns used to illuminate the object, thus resulting in a series of weighted light patterns which can be used to compute the image of the object. If an object is illuminated with short (below one hundred picosecond) light pulses and a light detector with sufficient temporal resolution is used, it becomes possible to reconstruct a 3-dimensional image of the object. Regrettably, this method mandates a compromise between the transverse resolution of the reconstructed image and the time required for gathering the measurement data as higher desired resolution also demands a greater number of light patterns projected onto the object.
One possible alternative for 3-dimensional imaging is a SPAD-camera (single-photon avalanche diode). A SPAD-camera employs an array of hyper-sensitive avalanche photodiodes which also enables the time of flight distance measuring of objects but in this case, transverse spatial information is obtained directly from the SPAD-camera’s pixels. Currently, the use of SPAD-cameras is limited by their relatively low resolution.
We propose a doctorate project which has a goal of developing a high speed high resolution 3D-imaging method based on applying single-pixel imaging principles to a SPAD-camera’s pixels. The thesis process utilizes cutting edge SPAD arrays developed by our Switzerland (EPFL) partners.
Supervisors: Toomas Plank
E-learning is generally seen as the source of innovation in all kinds of learning scenarios. However, there is a growing gap between visions and expectations from the one side and reality from the other – as scientific community discusses opportunities of Web 3.0 teachers still feel uncomfortable with basic ICT concepts and applications.
The next big step in web technology could be Semantic Web or web of data. According to the W3C, "The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries". In the context of e-Learning it would mean, that data and learning objects (LO) could be freely navigated, combined and used in all kind of learning situations from a single application by teacher or by an intelligent tutoring system. Also the concepts like massive reuse of LO’s, adaptive learning could be easily implemented.
In this doctoral project we examine the behaviour and expectation of physics teachers in searching, selecting, reusing and mixing of learning materials. On the basis of the study an iterative design process will be launched to create an adaptive, robust and user-friendly e-learning system with unique new capabilities.
Supervisors: Andi Hektor, Gert Hütsi, Margus Saal
The PhD project will investigate the physics of the cosmic 21cm radiation with a particular emphasis on aspects relevant for the fundamental physics. In particular, the main focus will be on high redshift radiation, emitted before the epoch of reionization. To a large extent this study is motivated by recent detection of an anomalously large absorption feature in the radio background by the EDGES experiment. If this measurement stands the test of time it will certainly be amongst the most significant cosmological discoveries of the decade. The strength of the measured signal cannot be accommodated in the standard cosmology. It can be a hint of new physical phenomena, e.g., non-canonical coupling between dark and baryonic sector. The 21-cm cosmology is a rapidly evolving research field with many ongoing (LOWFAR, EDGES, the SKA pathfinders etc) and future experiments, culminating with the ambitious SKA starting around 2025. Assuming the possibility to control the dominating foreground radiation (4 orders of magnitude above the signal!) the 21cm cosmology is expected to boost the field of observational cosmology as the CMB measurements have done during the last decades.
Institute of Chemistry, Ravila 14a, 50411, Tartu, Estonia. Phone: (+372) 737 5261, e-mail: chemistry [ät] ut.ee, web: www.chem.ut.ee
Supervisors: Kaido Tammeveski, Heiki Erikson
The demand for energy has increased significantly during the last century. Thereby huge effort has been put into the development of environmentally friendly efficient energy conversion devices. Fuel cells are one possible solution for soothing the energy demand, however, expensive platinum is used in those devices as catalyst for oxygen reduction reaction. Another possibility is to use metal-air batteries in which also oxygen evolution reaction is employed. Silver and silver-based catalysts have shown promising activity towards both reactions and thus in this project we aim to develop bifunctional silver-based catalyst for oxygen reduction reaction and oxygen evolution reaction. Hence, in this work cheap and more abundant silver is used as an alternative for expensive and scarce platinum for low-temperature fuel cell applications.
Supervisors: Ester Oras, Ivo Leito
Archaeological residue analysis is a rapidly developing field combining scientific laboratory methods for studying ancient material. The major branch of current research is the analysis of food-related molecules in archaeological ceramics. The project aims at employing novel high-resolution analytical techniques to identify low-concentration biomarkers in ancient food remains, including the combination of currently widely applied lipid residue analysis with novel protein identification. The project foresees establishing novel source- up to species-specific and also certain food procurement (fermentation) practices-related dietary biomarkers, and analyse particular food procurement practices reflected in various aging and degradation products.
Supervisors: Nadezda Kongi, Kaido Tammeveski
In this PhD project new classes of electrocatalyst materials for their use in sustainable energy conversion and storage devices will be developed. Motivated by the urgent need for improved, earth-abundant-based (i.e. Pt-free) catalysts, an original set of metal-organic frameworks (MOFs) based electrocatalysts will be designed and developed. This will be accomplished by customization of catalyst structures, involvement of different earth-abundant metals and developing the knowledge-based design of the electrocatalytically active sites. Multifunctional ability to efficiently catalyze simultaneously different oxygen and hydrogen electrochemical reactions will be explored by using state-of-the-art electrochemical techniques combined with physical characterisation methods.
Supervisors: Enn Lust, Rutha Jäger
Polymer electrolyte fuel cells and electrolysis cells are promising low temperature chemical energy/electricity conversion devices due to their high efficiency and zero/low emission of contaminants. Attention has been shifted toward developing more inexpensive and economically viable catalyst materials. Extensive efforts have been made to develop cost-effective alternatives based on more abundant and less expensive d-metals, d-metals alloys oxides, deposited onto specially designed carbon supports for developing the active sustainable electrodes for OER devices. Due to the cost-efficiency some novel FeNiX, FeCoX and FeCoNiX complex oxides deposited onto micro-mesoporous carbon supports and other supports, are under intensive studies at the time being. Novel approaches for deposition of nanostructural 3-d metal oxides and 3-d metal alloys oxide onto various carbon and non-carbon supports will be used and the OER reaction characteristics will be established. In this area, carbon materials (also carbon derived from Estonian well-decomposed peat) as a catalyst support will be applied.
Supervisors: Gunnar Nurk, Sergii Pylypko, Enn Lust
The aim of this project is utilization of novel economically attractive high speed screen-printing method for preparation of components for reversible solid oxide fuel cell and improvement of long term stability of this cell if operating at electrolysis mode. For this purpose the compositions of raw pastes for chemical barrier layer (based on gadolinia doped ceria) and electrolyte layer (based on yttria stabilized zirconia) will be optimized based on rheological requirements of high speed screen-printing technique. Optimized pastes will be used for preparation of unit cells. Special attention will be paid on the microstructure of the interface of chemical barrier layer and electrolyte layer because delamination of these layers is main reason of performance degradation of reversible solid oxide fuel cell operating at electrolysis mode. Properties of electrolyte/barrier layer interface will be designed by variation of paste compositions and thermal treatment programs. Additionally, the fuel electrode porosity will be optimized to increase the speed of water diffusion in the electrode. All mechanically stable membrane – electrode systems will be characterized electrochemically. In the case of best systems long term tests and detailed microstructural study will be performed.
Supervisors: Enn Lust, Jaak Nerut, Heili Kasuk
Fuel cell is an attractive device to convert chemical energy into electric energy. There are several types of fuel cells. Polymer electrolyte membrane fuel cell (PEMFC) is one of very promising FC that works at low temperature. Hydrogen and several organic compounds, including methanol and ethanol, could be used as fuels in PEMFC. The usage of ethanol fuel cells (DEFC) is not very widespread because the kinetics of ethanol oxidation is sluggish, and catalyst is very easily poisoned with ethanol decomposition products – mainly carbon monoxide. Therefore, it is essential to design novel bifunctional catalysts on which the decomposition rate of alcohol is high and at the same time the activity of the catalyst does not decrease in time. The aim of the project is to synthesize composite catalysts composing of cerium oxide and platinum. The catalyst support is carbon, which is derived from carbide, glycose or Estonian peat. The deposition of cerium oxide is assisted with various organic compounds e.g. different amino acids. In order to find out the functional relationship between the structure of catalysts and physical properties of catalysts the catalyst will be characterized using various physical and electrochemical methods. The most promising catalysts will be tested in single cell experiments.
Supervisors: Koit Herodes, Ivo Leito
Many compounds of biological relevance contain amino-functionality: most importantly amino acids, but also many pharmaceuticals (e.g antibiotics, antidepressants). As the living organisms can be extremely sentitive towards these compounds, their analysis at trace level is required in complex matrices (body fluids, food, environmental samples etc). For this purpose high performance liquid chromatography (LC) with UV-Vis, fluorescence (Fl) or mass spectrometric (MS) detection is often used. Due to polar nature of many of these compounds they are often difficult to separate in LC. Furthermore, many of them lack chromophoric, fluorophoric and ionizable group which hinders their sensitive detection. To improve LC separation and detectability derivatization of analytes is often used. In this work novel derivatization reagents will be synthesized and tested. The reagents are designed to possess high absorption in UV-Vis region, efficient fluorescence and ionizable group for MS detection. Such universal derivatization reagents are especially useful when many samples have to be screened – readily available LC-UV or LC-Fl instruments can be used for screening and LC-MS instrument for confirmation. Derivatization reagents will be developed on an example of amino acids and applied also for analysis of pharmaceuticals in environmental samples.
Supervisors: Kaido Tammeveski, Elo Kibena-Põldsepp
It is well-known that Pt-based catalyst materials for the oxygen reduction reaction (ORR) taking place on the cathode side of the fuel cell are the best so far. However, many disadvantages of the Pt-based catalysts (e.g limited availability and high cost of Pt, moderate durability of the Pt-based catalysts in the fuel cells) rather hinder the commercialisation of the fuel cell devices. Therefore, the aim of this PhD project is to synthesise low-cost, highly active (comparable with commercial Pt/C) and stable ORR catalysts based on M-N4 macrocycles (e.g. metal porphyrins and phthalocyanines) for the fuel cell applications. It is planned to use not only MN4 macrocycles, but also different carbon-based materials (e.g. graphene or graphene-related materials, carbon nanotubes, carbide-derived carbons) in combination with M-N4 macrocycles to prepare highly active composite materials for the ORR. The novelty of this work is that within this PhD project, special attention is paid to determine the nature and number of active sites on the surface of the catalysts, which is rather challenging since the M-N4-based catalysts are mostly with complex structure. However, the thorough knowledge about the nature and number of active sites would enable a rational design of MN4-based catalyst materials for the fuel cell applications. Therefore, special care will be taken in optimising the synthesis conditions of the catalysts and tuning the properties of the catalysts for the high catalytic activity and durability towards the ORR. In addition, the most promising M-N4-based catalysts will be tested in a fuel cell system.
Supervisors: Kaido Tämm
Nanomaterials are of importance for many industrial, medical and environmental applications as their properties are significantly different from the bulk material. Therefore the nanomaterials are applied in the products and processes where their specific properties have advantages over the properties of bulk materials. Environmental and health risk assessment is also a growing field of research. Therefore, within current project the existing methods for modelling of nanoparticles, such as QSAR, ANN, PCA etc., will be developed further. The methods for calculation of nanodescriptors will be expanded and made applicable for modelling of structurally wider selection of nanoparticles. Newly developed nanodescriptors will be used for modelling the biological activities of nanoparticles based on the experimental data from the literature and collaboration partners.
Supervisors: Ago Rinken, Leopold Parts
Muscarinic acetylcholine receptors, a class of G-protein coupled receptors, regulate many vital functions in both the central nervous system and in peripheral tissues. Although the receptor might seem to have a relatively simple structure the functionality of the protein is heavily regulated by different regulatory proteins and allosteric modulators. Important details about this regulation, however, remain uncovered to this date. This PhD project aims to integrate two rapidly developing interdisciplinary fields, high-resolution microscopy and systems biology, to solve this problem. Microscopy allows the measurement of a large variety of system-specific parameters while systems biology allows the theoretical description of the measurement results. During the project, we will compare the binding modes of different ligands to different subtypes of muscarinic acetylcholine receptors by using custom designed fluorescently labelled ligands. The measurements are carried out with both baculovirus particles as well as with the live cell system. For the purpose of the measurements, specific image analysis algorithms will be developed, which allow the quantitative analysis of the bioimages. Based on the measurements new systems biology models will be proposed to explain the measurement results. This holistic approach can, for example, uncover new ideas for drug design. In parallel to the measurements, the software created for bioimage analysis and systems biology will be generalized in order to be compatible to a wide array of other cutting edge software solutions while keeping the software easy to use. This will be achieved by specialized data formats, APIs and user interfaces.
Institute of Mathematics and Statistics, J. Liivi 2 - 513, 50409, Tartu, Estonia. Phone: 737 5863, 737 5453, e-mail: ltms [ät] ut.ee, web: math.ut.ee
Supervisors: Jüri Lember, Kristi Kuljus
A hidden Markov model (HMM) is a bivariate random process (X,Y), where Y is an underlying not observed (hidden) Markov chain and, given Y, the values of X – observations - are conditionally independent. Thus a path of Markov chain is observed with noise and often the goal of HMM-inference is to denoise it or, equivalently, to prognose a realisation of the hidden process based on the observations. This problem is called segmentation.
Two standard approaches to solve it are to apply the Viterbi algorithm to obtain the so-called Viterbi path or to apply forward-backward algorithms to obtain the so-called PMAP-path that minimizes the expected number of classification errors. These (and many other) algorithms might be applicable also when (X,Y) is any bivariate Markov process not necessarily an HMM. Such models are called pairwise Markov models (PMM). PMMs are richer model than HMM, allowing many interesting sub-models like Markov switching models or correlated Markov chains.
An even deeper model is a trivariate Markov process (X,Y,U) - triplet Markov model (TMM), where the third component U incorporates inhomogeneity to the model. When (X,Y,U) is a TMM, then (X,Y) is not necessarily a PMM and so the PMM-segmentation algorithms for (X,Y) cannot be applied anymore. In particular, the Viterbi algorithm does not work, but several stochastic and deterministic approximations have been worked out. Thre main objectives of the project is to study the segmentation for TMM, PMMs theoretically an practically: work out algorithms, study their properties and implement for real data.
Supervisors: Valdis Laan
The notion of Morita equivalence is one of the most useful tools to study properties of algebraic structures using their representations. Morita equivalence was first studied for unital rings, but later many other structures have also been considered. Our aim is to investigate Morita equivalence of factorisable semigroups. We are interested if one can use Schützenberger categories to describe Morita equivalence of such semigroups. If we succeed then we will try to find also other conditions equivalent to Morita equivalence. finally we will try to generalize the obtained results from unordered semigroups to ordered semigroups.
Supervisors: Arvet Pedas
The concept of the fractional (non-integer) order derivative, based on the inversion of the Riemann-Liouville integral operator, appeared a long time ago. However, at the beginning most of researchers have treated this concept as a useless curiosity. In the past years the attitude cardinally changed and the concept became very popular since it was noticed that in many problems of physics, chemistry, mechanics, biology, economics and other sciences and real-life processes, the differential equations with fractional derivatives express the reality more precisely than the classical differential equations with integer order derivatives. For most fractional differential equations, we cannot provide methods to find their solutions analytically and it is necessary to use numerical methods. While many methods are discussed in the literature, most analysis fails to mention the significant fact that solutions of these problems typically exhibit weak singularities, even when the data of the problem are smooth. Such analyses of smooth solutions are valid only for the small subclass of problems. Therefore, the main goal of the doctoral work is to design and justify methods for the numerical solution of linear and non-linear fractional differential equations in much difficult but typical case where solutions have weak singularities. In particular, one purpose is to develop collocation-based numerical methods and theory that is as general as possible. Actually, instead of standard piecewise polynomial collocation approximations we try to apply central part interpolation together with collocation on the uniform grid. This approach was successful for the numerical solution of Fredholm integral equations of the second kind, see . It showed some accuracy and numerical stability advantages compared with standard collocation methods. We try to use some ideas of  to construct effective numerical methods also for fractional differential equations. Moreover, we plan to extend some of our analysis to the case of linear systems of fractional differential equations.
More exactly, the following activities are under consideration: 1) study the existence and regularity of solutions of some classes of fractional differential equations and their systems (here we hope to publish at least 1 paper); 2) construction of higher order numerical methods which take into account the possible singular behaviour of the exact solution of the problem (2 papers); 3) numerical experiments (1 paper).
Supervisors: Jaan Lellep
Vibrations of arches made of nano-materials are investigated. It is assumed that the nano-arches have piece wise constant dimensions of cross sections .The arches are weakened by stable cracks or crack-like defects emanating from re-entrant corners of steps.The stress-strain state of the nano-arch is defined with the help of the non-local theory of elasticity of Eringen. According to the Eringen theory the stress state at the current point depends on the strain state at each point of the body. A general method of determination of eigenfrequencies of nano-arches is developed accounting for the existing defects. Natural frequencies of simply supported and clamped nano-arches are determined and the sensitivity of eigenfrequencies on the gometrical and physical parameters defined.
Institute of Molecular and Cell Biology, Riia 23, 23b - 134, 51010, Tartu, Estonia, Phone: (+372) 737 5011, web: www.tymri.ut.ee
Supervisors: Margus Leppik, Tiina Tamm
The expression of information encoded in genes is central to the development, function and adaptation of organisms. Thus, to ensure that the essential processes in cells take place, the expression of all genes must be very highly regulated and coordinated. Gene expression can be regulated in a number of steps, including post-transcriptional processing of mRNA.
The mRNA of eukaryotic organisms contain pseudouridines (Ψ) that are generated posttranscriptionally. It is known that Ψ in the stop codon of mRNA causes the loss of the protein synthesis termination signal, meaning that Ψ is able to alter the biological role of the stop codon. Majority of Ψ found, are in the mRNA coding sequence, and their occurrence is dependent on stress conditions, which is a direct indication to a biological importance. Still, current knowledge of the biological role of Ψ in mRNA is scarce.
The aim of current PhD project is to elucidate i) how pseudouridines in the coding region of mRNA affect the codon identity and the rate of protein synthesis and ii) how Ψ affect the scanning of the ribosome pre-initiation complex in the 5'-untranslated region (5'UTR) at the initiation step of protein synthesis. The doctoral project is expected to explain, a potential mechanism for gene expression regulation, not previously described. As there is a link between Ψ synthesis and cancer development in several human cancers, the PhD project has potential importance in medicine. The present PhD project also broadens the basic knowledge of molecular biology in the regulation of protein synthesis.
Supervisors: Maia Kivisaar, Heili Ilves, Jaanus Remme
The aim of the proposed doctoral project is to elucidate molecular mechanisms which are connected with elevated mutation frequency in pseudomonads lacking tRNA modifications in anticodon stem-loop (ASL). We are going to investigate whether the increased mutation frequency in the absence of pseudouridine synthases TruA or RluA could be associated with decreased translation fidelity in soil bacterium P. putida and human opportunistic pathogen P. aeruginosa. As the error frequency of translation has not been analysed in pseudomonads, we will compare translational accuracy in different bacterial species in the presence and absence of TruA or RluA. In addition, strains with reduced translation fidelity (obtained by replacing ribosomal protein genes with alleles of known effect on the translational accuracy) will be constructed and examined to explore a potential link between translational fidelity and mutation frequency. We will investigate whether the absence of pseudouridylation of ASL could affect evolvability of bacteria. For this purpose, we will perform various mutagenicity assays under stressful conditions of bacteria and assess the effects of the absence of pseudouridine synthases on pathogenicity and development of antibiotic resistance. We expect that the obtained results would be important to understand basic mechanisms underlying translational fidelity and mutagenicity in bacteria, and would provide insight into the mechanisms of the development of pathogenicity and antibiotic resistance in bacteria.
Supervisors: Jaak Truu
The main aim of the proposed study is to determine the main differences in key microbial species and metabolic pathways responsible for the degradation of different oil fractions in different marine compartments of the Baltic Sea and global marine environment (with emphasis on Northern-Atlantic Ocean). The study will build up knowledge and data bank on the microbial capacity to degrade oil compounds at taxonomic, functional and genomic levels in the global marine environment and provides specific knowledge about how microbes respond to the oil spill and degrade hydrocarbons in the Baltic Sea. The obtained information enables better predictions for intrinsic biodegradation capacity of oil fractions in sea water, sediments and coastal material for the Baltic Sea and allows assessing and developing specific mitigation approaches for the prevention of negative impact of oil pollution on important ecosystem functions such as nutrient cycling and hypolimnion hypoxia.
Supervisors: Viljar Jaks, Mariliis Klaas
Prolonged life expectancy and modern lifestyle-inflicted diseases have increased the need for tissue replacement in the Western countries. At present, the only acceptable cure for liver cirrhosis is a liver transplant; however, the demand for liver replacement now far outstrips the availability of transplantable organs. Liver regeneration in response to injury involves the restoration of functional liver tissue through cell proliferation and remodelling of the extracellular matrix (ECM). Similarly, the modification of skin ECM occurs during physiologic wound closure and several pathological processes. ECM is a dynamic structure composed of a variety of proteins and other macromolecules, which enable the cells to adhere and migrate by providing a physical growth substrate but also cell-matrix signalling critical for survival. Understanding the regulation of tissue regeneration at the level of cell-ECM interaction is of utmost importance in order to develop novel therapeutic approaches for restoring the function of damaged tissues.
We hypothesize that ECM plays a prominent role in regulating the proliferation-quiescence-differentiation balance of somatic stem cells in tissues such as liver and skin. Our previous work has identified the molecular alterations in liver ECM composition during liver regeneration using high throughput proteomic approach. Therefore, the specific aim of the proposed project is to clarify the role of these proteins in regulating cell fate decisions and differentiation potential tissue regulation as well as describe the molecular mechanisms behind these events.
Supervisors: Mayukh Mondal, Francois Xavier Ricaut, Richard Villems
Recent genetic studies have shown that the people living in Papua New Guinea are unique in many ways. They have lived in isolation from other populations throughout their last 50,000 years of history, and have thus gone through a separate path of evolution. In addition to introgression from Neanderthal that are common to all non-Africans, this population (and Australian Aborigines) are also have the greatest genomic contributors from Denisova (5%). In addition, we recently found that at least 2% of the Papal genome originates from an anatomically modern human migration from Africa, with no trace in other populations. The evolutionary history of the Papua New Guinea people is extremely interesting due to their living environment. They have had to adapt to very different conditions and environments in isolated areas. Cultural evolution, which has led to the survival of over 900 languages in a small area of global significance, also refers to clear structuring.
The overall plan of the doctoral thesis is to explain the nature of the genetic contribution of different human population in papal populations, to reconstruct the demographic history of Papuan people over the past 50,000 years, and to identify the genetic nature of natural selections. To do this we use the existing tools of modern population genetics and develop new methods. In collaboration with Toulouse University, we have access to 178 high-definition, unpublished papal genomes that, together with our computing and analytical capabilities, provide a sufficient material base for the successful completion of our doctoral thesis. In addition, the phenotypic data (18 attributes) have been provided for 120 gene expression samples per population, providing an opportunity to study genotype / phenotype relationships. This aspect is particularly important and novel, as samples of population genetic studies have traditionally been collected without phenotypes, which significantly narrows the possibilities for research in this direction.
Supervisors: Kristiina Tambets, Toomas Kivisild, Richard Villem
This project concentrates on the demographic history of the Medieval and Early Modern time layer (13th -18th ccAD) of the territory of Estonia using ancient DNA (aDNA) as the primary source of information. The Medieval period started in Estonia much later than in Central Europe and Scandinavia, on the 13th century AD. The crusades and conquest brought along vast social, cultural and economic changes that assumingly also changed the genetic structure of the local society. Genetic diversity of the Medieval Estonian rural and urban populations will be assessed and compared against earlier time layers and present-day variation using available aDNA and UTIG biobank data, as well as comparative data from elsewhere in Europe. We will combine this knowledge with the data of individual and societal health status through description of the presence and frequency of pathogens, which gives us clues to understanding the history of present-day health problems in Estonia. The outcome of the project will be used for filling one of the remaining gaps in the synopsis of the Estonian population history and for opening new opportunities associated with the studies of health and diseases through the aDNA perspective.
Supervisors: Osamu Shimmi
Animal development has been investigated through the analysis of tissue morphology. These events are regulated by reciprocal inductive tissue interactions. During last few decades molecular genetics approaches revealed mechanisms underlying tissue morphogenesis. These studies greatly enhanced our knowledge of how developmental signaling affects tissue shapes. However, despite the increasing knowledge of the molecular basis of tissue morphogenesis, how the activity of these signaling pathways is translated into changes in cell behavior and how cell shape changes affect developmental signaling remain poorly understood. Since morphogenesis involves dynamic cellular processes, tracking real-time changes in cell shapes must be crucial for further understanding these processes.
In this research project, we aim to address the logic of 3D morphogenesis, how simple 2D structure is rearranged into more complex 3D tissues, by employing in vivo 5D imaging techniques. We use Drosophila pupal wing, two-layered epithelia, as a 3D model. Our preliminary data indicate that this claim can be explored by two distinct but related mechanisms: cellular mechanisms coordinating 3D architecture formation, and coupling between developmental signaling and tissue shape changes. Exploring mechanisms underlying 3D morphogenesis will lead to novel insights into in vitro 3D organogenesis from stem cells as well as vertebrate development. These approaches will enhance our understanding in human diseases as well.
Supervisors: Priit Jõers
Mitochondria have diverse roles in the cellular metabolism: hosting the TCA cycle, controlling Ca2+ signaling, forming FeS clusters, inducing cell death to name but a few. However, their best known role is to generate ATP via oxidative phosphorylation (OXPHOS) by harnessing the free energy released by the electrons travelling along the respiratory chain (RC). Defects in this system lead to cell’s energy crisis (decrease in ATP synthesis) and overproduction of harmful reactive oxygen species that form when electrons in RC spontaneously interact with molecular oxygen. Mitochondrial pathologies or conditions caused by mitochondrial dysfunction are caused mainly by these two phenomena. However, there is an increasing amount of data demonstrating that changes induced in cell’s homeostasis by mitochondrial dysfunction are much more complex than just ATP/ROS-based phenomena and sometimes even bypass the OXPHOS function altogether. These can be intracellular events leading, for example to serine overproduction and resulting imbalance in one-carbon metabolism, or systemic, where whole organism’ catabolism is changed by endocrine signaling via fibroblast growth factor 21 (FGF21).
We have recently characterized a mitochondrial stress system that induces modest changes to Drosophila mitochondrial DNA (mtDNA) in vivo. This does not lead to collapse of OXPHOS, but rearranges metabolism in multiple drastic ways: catabolism is strongly shifted towards consumption of lipids due to inhibition of carbohydrate utilization and serine production from glycolysis is significantly increased. This highlights a completely novel role for mtDNA as a metabolic regulator in addition of being a carrier of genetic information. MtDNA exists in vivo in DNA-protein structures called nucleoids which have a complex and variable list of protein factors. Some of them are known enzymes of various metabolic pathways, which suggests a possibility how mtDNA stability might reprogram metabolism. However, direct evidence that nucleoid stability/contect is capable of changing metabolic balance is lacking in organisms beyond yeast.
We have also identified certain factors (Akt kinase) and phenomena (loss of cytonuclear protein acetylation) that cause some of these changes, but there are plenty unanswered questions. This doctoral student project seeks answers to following questions:
Answering these questions have much wider relevance to human medicine than just mitochondrial pathologies as serine overproduction is frequently see in tumors and is associated with poor prognosis in patients, while metabolic inflexibility in catabolic carbon source selection is emerging as a major cause in onset of metabolic conditions like diabetes.
Tartu Observatory, Observatooriumi 1, Tõravere, Phone (+372) 737 4510, e-mail: info [ät] to.ee
Supervisors: Mait Lang
National Forest Inventories (NFI) are used for regional level estimates of forest resources in many countries. The NFI-s are based on sparse network of field sample plots. Airborne laser scanning (ALS) and multispectral medium resolution satellite images widely used in Scandinavia for the construction of forest maps. The forest canopies in Estonia and Latvia are more complex and there are still no suitable models for ALS data processing for the NFI methodologies. The first aim of the research is to collect and test existing models from countries and also develop improved models suitable for local conditions. The second aim of the study is to search for machine learning methods that are applicable for processing of multispectral satellite images from Sentinel-2 MSI and Landsat-8 OLI together with NFI field samples for the construction of forest canopy structure maps.
Supervisors: Mihkel Pajusalu, Andris Slavinskis
Nanospacecraft are expected to revolutionize space missions by providing affordable research platforms for both remote sensing of Earth and exploration of deep space. The goal of this doctoral project is to develop a novel miniaturized Earth imager and an imager for mapping small solar system bodies during fly-by missions. The Earth imager is in early development as a part of European Space Agency’s Industry Incentive Scheme to provide a standardized radiometrically calibrated multispectral imager for scientific Earth observation purposes. The system will enable two spectral band coverage of Earth’s surface from a low Earth orbit using small, low cost, and disposable CubeSat platforms. The system will have novel integrated calibration mechanisms, which allow to calibrate the camera while on orbit for highly repeatable measurements. The second goal is to develop an imager for fly-by imaging of a comet’s nucleus or other similar targets. The instrument is currently being considered for European Space Agency’s F-class comet interceptor mission proposal. Comet flybys are especially challenging due to the extreme relative velocities and a hostile dust environment, which require a system that is both fast and robust. Both of these imagers can be used for different mission cases and can possibly even be commercialized for private Earth and deep-space missions.
Supervisors: Jukka Nevalainen, Elmo Tempel
The leading cosmological model makes a very precise prediction for the cosmic density of baryons, i.e. the normal matter. Only half of this has been observed in the nearby Universe. This introduces the serious current cosmological problem of the "missing baryons".
Cosmological simulations indicate that these missing baryons hide in a low-density plasma called WHIM (the Warm-Hot Intergalactic Medium) within the Cosmic Web filaments. At the expected WHIM temperatures of log T(K) = 6-7, the signals are at the X-ray wavelengths. Unfortunately, the low WHIM density renders the Xray signal very small compared to the capabilities of the current X-ray instruments. Our aim in this project is to improve the observational status of the WHIM and thus to revise the baryon budget of the local Universe. This would enable the testing of the WHIM as a solution to the important missing baryons problem. Our strategy is to study the regions where the WHIM is expected to be the hottest and the densest, i.e. where the X-ray signal is expected to be the highest. Such regions are the outskirts of clusters of galaxies where the clusters are connected to the filaments of the Cosmic Web (i.e. cluster-filament interfaces). The accretion of the surrounding material into the cluster is expected to take place along the filaments. The kinetic energy of the infalling WHIM baryons is converted into the thermal energy of the gas at the cluster-filament interface. The PhD candidate will test and fine-tune our cluster-filament interface detection tools (Spaghetti and meat balls) to optimally detect the hot spots of infalling WHIM. The fine-tuned tools will then be applied to existing optical spectroscopic galaxy survey SDSS to characterise the cluster-filament interfaces. The candidate will use this information to test the theoretical predictions that galaxy clusters are the nodes of the filamentary Cosmic Web and that the clusters grow by accretion of material along the filaments. The X-ray follow-up of the hot spots will be used to test the hypothesis that the WHIM has the missing baryons. The candidate will use the locations of the hottest and densest WHIM to construct WHIM finding maps for the future X-ray satellites eROSITA and ATHENA.
Institute of Technology, Nooruse 1, 50411, Tartu, Estonia. Phone: (+372) 737 4800, e-mail: info [ät] tuit.ut.ee,web: www.tuit.ut.ee
Supervisors: Andres Merits
lphaviruses (family Togaviridae) have positive strand RNA genomes and are transmitted between vertebrate hosts via mosquito, most commonly Aedes sp, vectors. The molecular bases of alphavirus vector specificity remain poorly understood. Medically most important alphaviruses are CHIKV, ONNV, MAYV, RRV, VEEV, BFV and SINV. SFV represents well studied non-pathogenic model alphavirus. Alphaviruses replicate in cytoplasm of infected cells using virus encoded replicase consisting from 4 subunits. We have developed advanced systems allowing reconstruction of functional replicase from its individual components. Topics include analysis of:
As the project is experimental in its nature and includes analysis of RNA replication by Northern blotting, analysis of interaction of replicase components by swapping, construction and use of CRISPR-Cas9 KO cells, experiments with recombinant viruses and transgenic cell lines.
Supervisors: Patric Jannasch, Lauri Vares
This project develops new sustainable platform for novel bio-derived polymers used in applications with strict demands for properties (e.g. automotive industry, coatings, packaging, etc). A widely available platform chemical from glucose containing biomass, citric acid, is used as a starting material. Citric acid is converted into bicyclic ketone, which is expected to yield polymers with high glass transition temperature and mechanical strength. Both polycondensation polymers and polymers produced via radical polymerization are investigated.
Supervisors: Tarmo Tamm, Uno Mäeorg
The main goal of the project is to develop a new generation of silicone foams of novel and/or qualitatively improved properties. The focus of the project will be on a) the improvement of mechanical strength while maintaining low density (0.15-0.1 g cm-3.) at the same time. The enabling technology is expected to be using computer simulations for modelling the foam structure formation as well as cross-link formation aspects. b) foams with anisotropic mechanical behaviour, including shape-memory effects. c) The barrier properties, in repsect to gas permeation, including water vapor and oxygen and d) selective sorption and adhesion properties, achieved by partial pyrolysis of the foams.
Supervisors: Arun Kumar Singh, Alvo Aabloo
Robots are gradually transitioning from confined factory floors to dynamic environments co-habited by humans leading to applications like collaborative manufacturing, autonomous driving. For robots to operate in these settings, they need the ability to compute optimal motion plans (how to move from point A to B) in (near) real time. A common approach has been to formulate motion planning as an optimization problem. A fundamental challenge in robotics is to make optimization based motion planning reliable and computationally efficient.
This is an important problem from not only academic standpoint but rather several companies like Energid aim to build a business around solving this problem. The challenge stems from the fact that most optimization problems encountered in robotics are non-linear and non-convex and hence it is difficult to postulate performance guarantees for these problems.
The proposed research aims to improve optimization based motion planning in terms of success rate and computation time. To this end, we would develop algorithms that exploits the niche computational structures of the problem which arise due to the specific kinematics or dynamics of the robots, nature of the application etc and leverage state of the art convex techniques. The developed algorithms would be bench-marked in applications like collaborative manufacturing, autonomous driving, multi-robot formation and object transportation etc.
Supervisors: Kaspar Valgepea
Due to the contribution of fossil-based industries to climate change, the world faces an increasing need for sustainable production of fuels and chemicals from renewable feedstocks. Recently, acetogen bacteria have attracted great interest as cell factories for converting inexpensive and abundant waste feedstocks (e.g. syngas [CO, H2, CO2] from gasified biomass, industrial waste gases) into high-value products using gas fermentation. Although acetogens arguably use the first carbon fixation pathway on Earth to fix CO2, better understanding of metabolism is needed for rational metabolic engineering. This project builds upon a unique opportunity to access a large-scale strain library of a model acetogen. We aim to address knowledge gaps in acetogen metabolism by performing systems-level quantification of acetogen genotype-phenotype relationships. We hypothesise that coupling gas fermentation with integrated -omics (e.g. metabolomics, proteomics) and computational (e.g. metabolic modelling, machine learning) analyses will notably advance understanding of acetogen metabolism and accelerate their engineering into superior cell factories.
Supervisors: Reet Kurg
Cancer is a major world-wide problem of public health as its incidence is increasing, but the results of treatments still remain unsatisfactory, due to development of tumor resistance to current therapies. So, the fundamental studies of cancer biology for understanding of this resistance are still needed. Currently, immunotherapy is considered the most perspective field for anticancer research. We are targeting the cancer-testis antigen MAGEA family proteins, which are cancer specific being an ideal target for cancer immunotherapy. The specific aims are: i) to characterize MAGEA-positive extracellular vesicles and their role in cancer progression; ii) to investigate the role of MAGEA proteins in genomic stability and DNA double-strand break response, and iii) in cellular senescence and senescence associated secretory phenotype (SASP). The knowledge about molecular functions of MAGEA molecular functions is required for development of biological therapeutics against MAGEA-positive tumors.
Supervisors: Ülo Langel, Kaido Kurrikoff
The project aims to use cell penetrating peptides (CPP) in conjunction with the exosomes as drug delivery system. CPP offer efficient trans-barrier delivery for various biomolecules, while the exosomes are natural entities with high biocompatibility. The combination allows potential utilization of the best from both worlds, i.e. achieve efficient drug delivery with no toxic side effects.
Supervisors: Hannes Kollist, Hanna Hõrak, Dmitry Yarmolinsky
Plants use solar energy to transform ambient CO2 into organic matter and this provides food and fiber for humankind. Designing high-yielding varieties adapted to the challenges associated with climate change is an urgent priority. Stomata formed by pairs of guard cells are small pores on the surfaces of plant leaves and stems that control plant gas exchange. Guard cells have evolved systems to sense and integrate various signals to optimize the balance between the two major processes of plant growth – CO2 fixation in photosynthesis and water loss via transpiration. We have recently shown that mitogen activated protein kinases MPK4 and MPK12 together with protein kinase HT1 form a molecular switch that is required for stomatal movements triggered by changes in ambient concentrations of CO2. Now we have identified several new mutations that impair CO2-induced stomatal regulation, including mutations in MPK12 and HT1 by which we can either increase or reduce plant water use efficiency and at the same time prevent stomatal closure by elevated CO2 that can suppress growth. Thus there is a significant potential in studying HT1/MPK module for breeding crops that would be water-saving in future world with elevated concentrations of CO2. The aim of this project is to study CO2-induced stomatal movements with the particular focus on gaining further mechanistic insight for the HT1/MPK module in Arabidopsis and tomato. The proposed project will pave the way to tackle two major future issues in agriculture: increasing ambient CO2 concentrations and water shortage.
Supervisors: Mart Loog, Siim Salmar
Lignocellulosic biomass is the most abundant renewable source of carbon and aromatic compounds. It is comprised of cellulose, hemicellulose and lignin, which can be converted into biofuels or novel chemicals. The project will be a joint effort and collaboration partly financed by the regional flagship wood refining company Graanul Biotech, and the recently formed laboratory of wood chemistry and bioprocessing at the Institutes of Technology and Institute of Chemistry. However, the industrial processes for lignocellulose valorization pose many challenges, such as high costs and need to optimize the conditions for chemical treatment, cellulases, lignin modifying enzymes, and microbial cell factories. The main objective of this PhD project is to increase the productivity of industrial technologies aimed to valorize lignocellulosic biomass from wood. The first objective is to find better solutions for lignin- valorization technologies. Lignin is the largest renewable source of aromatic compounds and can represent up to 35% of dry biomass weight, but requires chemical and biological treatment in order to break down the polymer. Every type of lignocellulosic biomass requires an individualistic approach. The project aims to solubilization and depolymerization of lignin. The second main objective is to optimize hydrolysis and cultivation of microbial cell factories to use of lignocellulosic sugars as substrates for production of high value chemicals. In conclusion, such a joint PhD project between industry and the university would be one of the first precedents of its kind aiming towards maximal valorization of all three main components of our most abundant renewable resource, the lignocellulosic biomass.
Supervisors: Tanel Tenson, Niilo Kaldalu, Yasuhiko Irie
In chronic infections, e.g. in the airways of the cystic fibrosis patients, bacteria develop antibiotic resistance that is often caused by decreased permeability of the bacterial cell wall. We are planning to screen a chemical library for compounds that restore antibiotic sensitivity of the drug resistant Pseuomonas aeruginosa isolates. If we find such compounds, we will try to identify their targets and molecular mechanisms that are responsible for sensitising the bacteria to antibiotics. Finally, we will test the effect of the hit compounds on antibiotic sensitivity of P. aeruginosa aggregate culture that is mimicking a chronic airway infection.
Supervisors: Vahur Zadin, Sergei Vlassov (FY), Alvo Aabloo
Projekti eesmärgiks on arendada eksperimentaalselt verifitseeritud multiskaala simulatsioonimetoodika materjalide uuringuteks heterogeensetes välistingimustes nagu kõrged elektriväljad. Projekt keskendub materjali nanostruktuursetel muutustele rakendades nii molekulaardünaamikad, tihedusfunktsionaali teooriat kui ka lõplike elementide meetodit selgitamaks selgitamaks väliste elektriväljade mõju aatomitevahelisele interaktsioonile. Eksperimentaalses osas rakendatakse reaalajas elektronmikroskoopiat arvutuslike tulemuste verifitseerimisek. Projekti tulemusena luuakse tarkvaraamistik mis võimaldab vajadusepõhist ning automatiseeritud nanostrutkuuride disaini mis on võtmetähtsusega komponent uute materjaliteaduslike ja nanotehnoloogiliste arenduste läbiviimisel. Mõningad projekti tulemuste rakendused on näiteks kompaktne CERN’is välja töötatav uus kiirendi lineaarpõrguti (CLIC) ning selle kiirendavate struktuuride disain, kõrgeid elektrivälju rakendavad kõrgeid elektrivälju rakendavate seadmete (n. radarid, osakestekiirendid, meditsiinilise kiirguse allikad, satelliitide komponendid, uudsed mikro- ja nanoprintimise lahendused) töövõimet, võimsust ning vähendada nende suurust.
Supervisors: Kaido Kurrikoff
During the doctoral project, a new method will be developed to achieve an efficient conjugation of a chemically synthesized peptide nanoparticle and a biologically synthesized protein. Such a method is an input to developing novel type of targeted drug delivery vector.
Supervisors: Tanel Tenson, Niilo Kaldalu, Marta Putrinš
Persister bacteria are insensitive to killing by antibiotics, facilitate the evolution of resistance, and undermine antimicrobial therapy of chronic infections. Decreased antibiotic influx and/or increased efflux reportedly have a role in persister formation. We are planning to screen a chemical library for compounds that facilitate antibiotic penetration into bacteria and enhance killing of persisters. If we find such compounds, we will try to identify their targets and molecular mechanisms that are responsible for sensitising the bacteria to antibiotics. Finally, we will test the effect of the hit compounds and cell penetrating peptides on antibiotic sensitivity of intracellular bacteria in model cell cultures.
Supervisors: Tarmo Tamm, Kaija Põhako-Esko, Indrek Must
The decades-long research on actuators and sensors based on electroactive polymers is today reaching its first practical use cases. To date, limited performance, efficiency, and stability have limited their application. The aim of this PhD project is to solve this gap by introducing new materials and methods. The introduction of ionic liquids revolutionized the application of electroactive polymers a decade ago; however, only ionic liquids of the second generation have been used to date. In contrast, the ionic liquids from the third generation not only demonstrate lower viscosities and higher conductivities but can also be tuned for the particular application. Despite understanding the high significance of matching the properties of electroactive polymers to the particular ionic liquid, very limited attempts have been made to match the properties of the electroactive polymer to the electrolyte for improved actuation performance. The aim of this project is to optimize the actuation parameters of electroactive polymers by tuning the synthesis parameters and by the introduction of selective additives.
Supervisors: Saoni Banerji, Alvo Aabloo, Jaan Raik (Taltech)
Otitis Media (OM), known as the second most reason after common cold for pediatric clinic visits, is an inflammatory disease of the middle ear that commonly affects pediatric populations. Acute OM (AOM) is characterized by bulging of the tympanic membrane due to bacterial infection while OM effusion (OME) does not exhibit signs of acute infection (as in case of AOM), but may lead to hearing impairment. Mistaking AOM with OME leads to the unnecessary prescription of antibiotics resulting in treatment failure and problems of antibiotic resistance. As a result, patients are overtreated with worst-case assumption and the inability to avail high-resolution structural and/or molecular imaging is particularly glaring resulting in complicated and erratic diagnosis. The accuracy of currently available methods are limited, cost-prohibitive and requires high skills. This demands an appropriate non-invasive solution for diagnosis, that can eliminate the overdiagnosis of patients. The solution should be targeted for primary care physicians and home use.
This project proposes to develop a user-friendly image-guided micro flexible robot incorporated with a drug-delivery mechanism. It is intended to operate in two phases: position-detection by imaging; and drug delivery. In the first phase, the proposed device should precisely track the infected site of OM in the middle ear (detect and characterize AOM from OME). This employs an integration of an ionic electromechanically active polymer (iEAP) actuator having a higher degree of freedom (DOF) and a microscale InGaAs sensor integrated with CMOS readout integrated circuit (IC). In the second phase, given that the targeted site is correctly detected, delivery of drug flux is administered, if required.
Supervisors: Janno Torop, Alvo Aabloo
This project focuses on liquid-electrolyte storage and separation technology development. The project includes both computer simulations of an electrolytic flow cell and experimental design of prototype based on circulating fluid material. Aforementioned energy storage solution and the selective accumulation of charged particles are a prerequisite for achieving technological leap, thus, ensuring better availability of alternative energy. In addition, novel findings in this area would allow large-scale development of storage devices and ensure integration with applications primarily related to alternative energy sources.
Supervisors: Arto Pulk, Kalle Kipper
The structural biology group is studying the localized protein synthesis in neurons that is shown to be important for long-term memory formation, synaptic plasticity, and RNA granule associated neurodegenerative disease. In polarized cells, such as neurons, the synthesis of an mRNA does not ensure its proper cellular expression. Most mature transcripts require the association with RNA-binding proteins (RBP), resulting in the formation of RNA granules, which are then transported within the cytoplasm along the cytoskeleton and delivered to their proper subcellular locations, where they can be locally translated. In addition to mRNA and RBP, localized RNA granules in axons and dendrites contain ribosomes. This macromolecular complex is collectively known as neuronal RNA granule. The main interest of the project is to shed a light on structural aspects of RBPs mediated mRNA inactivation in the neuronal RNA granules by using latest advances in the cryo-electron microscopy (cryo-EM), deep-sequencing or mass-spectrometry. Results would help to understand the complexity of RNA granules in neurons.
Institute of Ecology and Earth Sciences, Vanemuise 46, 51014, Tartu, Estonia. Phone: (+372) 737 5835, e-mail: om [ät] ut.ee, fax: 737 5822, web: www.omi.ut.ee
Supervisors: Urmas Kõljalg
Currently, microbial community studies are utilizing different approaches for the delimitation and communication of species. This makes it problematic to compare, reproduce and communicate the results. In the field of mycology, the Species Hypothesis (SH) paradigm, as implemented in UNITE (https://unite.ut.ee ), provides a stable and automated system for species delimitation and communication. It is developed by the global team of taxonomists, informaticians and geneticists lead by Prof. Kõljalg. UNITE allows to identify and communicate DNA sequence based species via DOIs (Digital Objective Identifier). The system is used by the most high-throughput sequencing analytical pipelines as well as by major biodiversity and genetic data portals GBIF (https://www.gbif.org ) and NCBI (https://www.ncbi.nlm.nih.gov/nucleotide/ ). Biosecurity is a growing issue internationally, where the dispersal of invasive (alien) species are one important aspect. Compared to invasive plants and animals, less attention has been paid to invasive fungi, partly because of their inconspicuousness, but their impacts can be profound. Identification and communication of invasive fungal species can rely only on genetic marker(s) and standard digital identifiers. Successful PhD student will work with international team: i) to develope further UNITE SH paradigm and ii) will detect and communicate invasive fungal species based on tools provided by UNITE and PlutoF (https://plutof.ut.ee ).
Supervisors: Kristjan Zobel
The general knowledge about coexistence mechanisms in multi-species stands should be adapted to the environmental conditions available in an ecosystem. At the same time it is evident that the nature of a community of co-inhabitants is largely a product of the set of traits in the assemblage of species in the species pool. We try to elucidate to what degree does the outcome of collective living depend on the ability of coexisting species to plastically adapt to ruling environmental conditions. We mainly focus on shoot morphological plasticity in herbs – the inherent capability of coexisting plants to modify their anatomy according to the particular environment they are facing during ontogenesis. We plan to run several common garden experiments, and also ones based on experimental manipulation of already established species-rich communities, in order to test the hypothesis that morphological plasticity could be the key trait for explaining diversity in dense multi-species communities. We expect to find high species diversity in spots where there is a “high concentration” of plastic species, when compared to ones under “non-plastic species rule”. We hope to find evidence supporting the idea that a positive relationship between local diversity and average species plasticity would be among the main forces shaping plant community structure.
Supervisors: Valentina Sagris, Jaak Jaagus
Heat waves are reaching our cities more frequently nowadays. They magnify the effect of so-called Urban Heat Island (UHI). Recent studies in Europe have shown that UHIs affect not only big urban agglomerations but they occur also in medium and small-size cities. Magnitude of the phenomenon depends on the presence of impervious land cover, built urban morphology and landscape composition. A widely accepted means to detect UHI is the use of satellite derived Land Surface Temperature (LST) and underling surfaces represented via land cover data or 3D built environment models. This project will concentrate on effects of UHI at three different scales. First, it will concentrate on wide scale of the heat waves effects (2018 summer) in cities in Northern Europe and Baltic region. Second, at intermediate scale, magnitude and morphology of UHI in selected cities (first candidates are Tallinn, Tartu and Helsinki) and influence of cities landscape composition on UHI will be investigated. Third, at the detailed scale, effects of UHI in context of built-up space will be modelled.
Supervisors: Age Poom, Kiira Mõisja, Hans Orru
The PhD project aims to produce a better understanding of the associations between urban mobility and environmental exposure to urban greenspaces and health risks by capturing human spatial behaviour with the help of long-term GPS datasets in different urban environments and social contexts. Urban green and blue spaces are key substitutes for natural environment for urban residents and emerging literature has documented a positive association between exposure to nature, and human health and well-being. At the same time, urban air pollutants are important drivers of adverse health effects and their spatiotemporal variability is typically neglected in environmental health research.
While conventional approach to environmental exposure analysis uses static, residence-based perspective, this PhD project aims to develop dynamic, actual exposure assessment methodology. This enables to overcome the uncertain geographic context problem raised by both spatial and temporal scale as people spend a considerable amount of time away from their residence. The PhD project applies contemporary location-aware technologies and geo-computational methods in the research field of time-geography.
Supervisors: Anneli Kährik, Tiit Tammaru, Kadri Leetmaa
European cities have become socio-economically and ethnically more unequal and spatially segregated over the last decades. Segregation generally has a strong connotation with a residential location. But residential segregation is often linked to other life domains, such as schools and workplaces. For example, residential neighbourhoods and their location can shape the choice of school, whereas both residential and school context plays a role on individual’s social and labour market outcomes. Neighbourhood and school choices, in turn, can be shaped by policies, but also by individual economic resources and preferences. The PhD project will lead to a better understanding of the dynamics and complexities of segregation, focusing on the transmittances of the (dis)advantages of segregation in one domain to the other(s). It will rely on the longitudinal individual-level registry-based database and longitudinal analyses. The data will allow spatially-detailed empirical studies. The first paper will investigate the role of school ethnic exposure on young peoples’ neighbourhood and housing careers during the adulthood. The focus will be on those young people for whom Russian language is a mother tongue, and who grew up in similar type of urban neighbourhoods – large housing estates. The second paper will focus on the effects of better integration on the labor market and increase in incomes on spatial integration. The third paper will focus on the role of ethnic own group exposure in residential neighbourhoods and schools on social mobility and labour market outcomes.
Supervisors: Kaido Soosaar, Ülo Mander
Existing models for nitrous oxide emission (various modifications of DNDC, DayCent, SWAT-GHG, fuzzy logic models, etc) will be enhanced and used for description and prediction of N2 and N2O fluxes in wetlands and forests grown on organic soils. Data sampled using the static chamber method in various climate regions of the world serve as a basis for the modelling. For determining gaseous N budget of forests, long-term (2 years) eddy covariance data from a deciduous forest will be used. Additional sampling for determining N2:N2O ratio and N2O isotopomer structure in selected forests will be conducted. Also, peat samples from various peatland types will be analyzed for abundance and structure of denitrifiers, and functional genes controlling denitrification (nirK, nirS, nosZ I&II) and anammox. Eddy covariance and automatic chambers in combination with Picarro and Aerodyne quantum cascade laser systems will be used to determine continuous fluxes of N2O in selected forests during the water table manipulation experiments. All the data gathered will be integrated in existing models of N2O emissions from wetlands and forests. Ecosystem-level models will be upgraded to the landscape level using the soil and land use data and GIS models. All the data gathered will serve for better management of forest ecosystems in terms of mitigation and minimising of greenhouse gas emissions.
Supervisors: Ivika Ostonen-Märtin, Marika Truu, Boris Rewald (Vienna)
Climate change affects Arctic and Subarctic ecosystems more than any other ecosystem in the world. The EU-funded Innovative Training Network FutureArctic - A glimpse into the Arctic future: equipping a unique natural experiment for next-generation ecosystem research embeds ecosystem research challenge directly in an inter-sectoral training initiative for early-stage researchers, that aims to form “ecosystem-of-things” scientists and engineers. FutureArctic aims to quantify how much carbon will escape from the Arctic in future climate. How do the multitude of ecosystem processes, driven by plant growth, microbial activities and soil characteristics, interact to determine soil carbon storage capacity? A group of fifteen PhD-students (Early Stage Researchers, ESRs) will study the ForHot ecosystem in Iceland, where a natural coincidence has provided us with the exceptional opportunity to actually look into the future.
Given the strong urgency of tackling and managing the climate challenge and the particularly important role herein of (sub)Arctic ecosystems, a rapid assessment of the ecosystem and ambient processes in this natural laboratory is essential. FutureArctic will achieve this challenge by adopting the fast advances made in the field of machine learning and artificial intelligence (AI), unmanned aerial vehicles (UAV) and (remote) sensor technology into environmental research at the ecosystem scale, into a new concept of an ‘ecosystem-of-things’ (EoT).
FutureArctic thus aims to channel an important evolution to automated machine-assisted fundamental environmental research. This is achieved through dedicated training of researchers with profiles at the inter-sectoral edge of computer science, artificial intelligence, environmental and agricultural science, sensor engineering and communication and social sciences. FutureArctic training ensures the development of unique enviro-technological job profiles, all with their own specialty, embedded in holistic knowledge on connected high-data throughput ecosystem research, ready for machine-assisted environmental ecosystem science and modelling.
More information and other vacant positions can be found on www.futurearctic.eu
Your PhD project: The ForHot (www.forhot.is) site offers a geothermally controlled soil temperature warming gradient in the subarctic grasslands, where the ecosystem processes are affected by the temperature increases expected due to the climate change. Reference plots, 10-year warmed plots and plots that have been affected by the elevated temperature of more than 45 years, allow to study both short and long-term responses to future climate change today.
You (ESR3 in FutureArctic) will work with plant roots and focus on the root-rhizobiome interactions along soil warming gradients in grasslands. A particular interest will be paid on the adaption mechanisms in the belowground - the focus of the work lies on the assessment of the root traits, such as plant species-specific changes in root biomass, production and turnover rates as well as on the role of associated partners within root-rhizobiome (e.g. roots, mycorrhizae, archaea) in resource uptake and on the analysis of the adaptation ability of root-rhizobiome of grasslands along soil warming gradient (from ambient to +15 C). This is studied together with root phenology (onset, peak and cessation of root growth and synchronization between shoot and root growth), root system morphology and root physiology.
Additional benefits will be expected from the synergic interactions between the PhD students (15) involved in this project and from the experience of working in different scientific groups and using versatile lab equipment as well as participating in developing of new methodologies and combining expertize. You will embark on secondments to other FutureArctic partners (UNIVIE, UAntwerpen and VSI), to integrate soil microbiome and rhizobiome functionality insights in a microbial soil organic matter turnover model and to parameterize root imaging for market-ready solutions for non-destructive rhizobiome assessments (in cooperation with prof Boris Rewald (VSI) and ESR12).
H2020 MSCA Mobility Rule: researchers must not have resided or carried out their main activity (work, studies, etc.) in Estonia for more than 12 months in the 3 years immediately before the recruitment
Supervisors: Ülo Mander, Mikk Espenberg
Worldwide, groundwater (GW) is often polluted by human activities, especially agriculture. In areas with intensive agriculture and fertilizations, GW is often polluted with excessive amount of nitrate (NO3). Water is undrinkable, if its NO3 concentration is over 50 mg/L. Constructed wetland (CW) technology can be used to remove NO3 from water. It is mainly mediated by the denitrification process, an anaerobic NO3 removal via microbial reduction which ends with the emission of molecular nitrogen (N2) and/or nitrous oxide (N2O). Denitrifying microbes need both anaerobic conditions, and organic matter to complete the denitrification processes. In cases with lack of organic matter microbial fuel cell (bioelectrochemical) technology can be used for removal of NO3 with autotrophic denitrification. To carry out this process, a system with cathode, anode and electric current is in use. Anode will act as electron acceptor and electrons are taken from water molecules. The electrons are lead to cathode where they divide water molecule into hydroxyl ion and molecular hydrogen. Hydrogen will be available for autotrophic denitrifying microbes and they can use it as an alternative energy source to reduce NO3 into N2O and N2.
Although the combined CW-bioelectrochemical system is already well-known, there is a limited number of studies on the microbial community structure and abundance in these systems. Beside the study how electric current will enhance denitrification intensity, we also will analyse the dynamics of microbial compositions during the NO3 removal experiments from both GW and NO3-rich treated wastewater. Both lab-scale and field experiments in two pilot-systems will be carried out. Various substrates and microbial compositions will be comparatively analysed. In lab-experiments water and gas samples will be taken weekly and microbial samples monthly, whereas during the field experiments water and gas samples will be taken twice per month and microbial samples four times a year. Physico-chemical analyses of water and substrate samples will be provided in both field and lab systems. In samples of CW filter materials and water, the abundance and structure of microbes possessing genes regulating various pathways of nitrogen cycle - denitrifying genes nirK, nirS, and nosZ I & II), DNRA regulating genes nrfA, nitrifying genes amoA (for both bacteria and archaea), comammox and anammox genes - will be determined; the qPCR and metagenomic analysis will be provided. Greenhouse gas emissions will be determined using static closed chamber/GC method and automated chamber/laser analyser; N2 emission will be analysed with He-O method.
Supervisors: Tõnu Meidla
The project is focussed on palaeocommunity reconstruction across the critical event horizons in the succession of Late Ordovician limestones that contain rich fossil marine fauna of excellent preservation. The sedimentary bedrock of this area is preserving evidence of dramatic climatic changes caused by a combination of palaeogeographic changes (continental drift into tropics), climate oscillations and several rapid environmental perturbations (volcanic and regressive events). The work will be based on paleoecological field observations and interpretation of unpublished quantitative data on distribution of several fossil groups. Reconstructing of pre-event baseline palaeocommunities and comparing likely consequences of the events with data on actual changes in the community structure, we intend to complement the Late Ordovician environmental history of the area.
Supervisors: Miia Rannikmäe, Regina Soobard, Karin Täht
Studies show that students often possess an alternative epistemology that is different from the experts. This, however, teachers don`t then to acknowledge. Students do not understand the role of ideas and a theory-building nature of science, and think the purpose of science is to gain a body of knowledge and undertake activities. Holding such limited epistemic understanding about science, students may have little motivation to learn science; they may not understand how to produce and improve ideas based on evidence, or construct a new idea, based on existing ideas. This may lead towards poor achievement in science and mathematics and even steering students away from science, mathematics and science-related careers. The current project targets discourse analyses to explore student`s epistemology in science and mathematics so as to explore cultural (Estonian and Russian school students) similarities and differences. An extencive analyses of the literature on existing instruments for measuring students’ understanding of epistemology of science and mathematics will be carried out. Using PISA 2015 data secondary analyses will be carried out to develop initial work models and based on those theoretically justified tools for measuring grade 9 students’ understanding of the epistemology of science and mathematics; their attitudes towards science and mathematics learning and their willingness to choose science-related careers will be developed. Finally Cmap methodology on knowledge-building discourse and epistemic reflection to validate the psychometric models will be applied.
Supervisors: Toomas Tammaru, Mohamed Ghamizi (Morocco)
Monitoring projects on insects, especially Lepidoptera, are increasingly used as a tool in conservation-oriented research. The aim of the present project is to create the necessary basis for a large-scale application of nocturnal Lepidoptera (moth) surveys in northern Africa. Using bait traps, moths will be sampled in mountainous areas of Morocco to study 1) moth diversity in different vegetation types, 2) the effect of human activities on moth biodiversity, 3) the effect of light pollution on moth assemblages, 4) high altitude species especially vulnerable to climate change. Additionally, host plant use of potentially endangered moth species will be experimentally assessed.
Supervisors: Vallo Tilgar
Many animals, especially birds, use sounds for communication, territory defence, mate attraction and warning conspecifics against predators. A loud noise can be perceived by parents as threatening or disturbing and can mask receiving acoustic signals from other individuals. Recent studies show that birds living in noisy environments increase the amplitude and frequency of songs and change daily singing activity. Previous correlative studies have reported negative effects of noise pollution to nest site selection and reproductive behaviours. The main objective of the doctoral project is to explore the effect of anthropogenic noise on individual behavioural patterns, reproductive success, male-male competition in singing and the transmission of acoustic signals (alarm calls) at the community level in free-living birds. The results of the project improve our understanding of mechanisms in how noise pollution causes non-adaptive changes in avian reproductive behaviour, sexual selection and antipredator behaviour. The experimental part of the project investigates the effects of different types of noise (traffic, chain saw, lawnmower) on incubation, provisioning behaviour and social interactions. The quasi-experimental approach focuses on the associations of natural noise levels with nest site selection, physiological stress levels and breeding success. Moreover, the outcome of the project enables the assessment of the sensitivity of behavioural phenotypes towards noise effects by quantifying physiological markers such as corticosterone and serotonin. The results of the project also offer novel approaches to improve the methods of conservation of endangered species.
Supervisors: Leho Tedersoo, Raivo Jaaniso (FY), Uno Mäeorg (KT)
Mycorrhizal fungi play key roles in plant mineral nutrition and mediating soil geochemical processes. Mycorrhizal fungi are capable of taking up simple organic compounds and transporting these to plant tissues, but the speed, pathways and regulation are so far poorly understood. This situation is more complicated, because in natural systems there are multiple plant and fungal partners interacting, which leaves nutrient exchange between partners regulated by the biological market. Typically, the amount of nutrients or stable/radioactive isotope tracers are extracted on selective harvesting, but this provides little information about the localisation of nutrients especially in root tissues. For these aspects, recently developed fluorescent nanotechnological tools such as quantum dots and carbon dots offer great promise in real-time tracking and quantifying nutrients, with a possibility of following three of more nutrients simultaneously. So far, the flow of quantum dot-tagged nitrogen compounds have been simply traced in mycelium and roots based on fixed material, but modern sensors integrated with microscopes, cameras and specific software offer much more opportunities.
The objectives of this project are several-fold:
1. Comparison of properties of commercially available Quantum dots with in-house synthesized Carbon dots in terms of minimum size, maximum fluorescence, maximum bonding with organic nutrients and interference with physiological processes of prokaryotes, fungi and plants as based on transcriptomics.
2. Developing methods for optimal measurement of Quantum/Carbon dots and fixed material and seeking opportunities to trace material flow in real time.
3. Quantification of nutrient flow from fungi to plants in paired conditions and in biological market conditions to understand nutrient trading mechanisms.
4. Seek answer to the question whether mycorrhizal types differ in regulation of nutrient exchange.
Supervisors: Toomas Esperk
Because of their high nutritional value, high feed conversion efficiencies and low emission of greenhouse gases, insects are considered a promising and sustainable system in producing food for humans and feed for production animals. However, benefits and costs of rearing insects for consumption are still not fully evaluated and several important aspects accompanying mass production of insects are clearly understudied. In particular, the effects of rearing densities on life history traits, nutritional composition of the insects and susceptibility to pathogens from the one hand, and the suitability of the commercially important traits as targets of selection on the other have remained insufficiently explored. The proposed doctoral project will examine these understudied topics in taking advantage of an established culture of the black soldier fly (Hermetia illucens), one of the most highly valued insect species for animal feed production. The thesis work is planned to consist of four relatively autonomous studies that will all be published as separate case studies in the peer-reviewed scholarly journals. The first study will aim to find out the optimal rearing densities for black soldier fly by rearing the larvae on several different density treatments and recording various life history traits at different developmental stages. The objective of the second part of the thesis is to examine the density effects on the immune response and disease susceptibility. The third study will inspect the responses of various traits to experimental evolution in different rearing densities. The fourth part of the thesis will evaluate the potential for evolving towards higher pupal mass, with the correlated changes in other life history traits being recorded. By addressing the density dependent effects and selection potential in a commercially important insect species, the proposed project has a high applied value while, through detailed examination of plastic and evolutionary changes in life history traits, it will also contribute to basic research in the field of evolutionary ecology.
Supervisors: Kadri Koorem, Maarja Öpik
Man-made changes in land-use are threatening biodiversity, especially in soils where the diversity of organisms is extremely high. Microscopic arbuscular mycorrhizal (AM) fungi, which live in the soil, are of key importance as they live in association with plant roots and can directly influence plant productivity. Despite of their importance, the effect of different disturbance types (eg. mechanical disturbance, fertilization, pesticide addition) on AM fungal communities remains unclear.
The aim of this PhD project is to use up-to date molecular methods and experimental studies to disentangle the effect of different disturbance types on AM fungal communities and their restoration potential. The experimental tasks of this project will focus simultaneously on AM fungal communities in agricultural fields and in natural ecosystems, using cultivated plant species and wild plant species as test plants.
The results of this PhD project enables to create sustainable agricultural practices and restore diverse AM fungal communities. Altogether these results are important for mitigating the effects of land-use change and preserving sustainable ecosystems.
Supervisors: Carlos Guillermo Bueno, John Davison, Maarja Öpik
Mycorrhiza – the association between plant roots and soil fungi - is among the most important terrestrial ecological phenomena; influencing plant and mycorrhizal fungal performance, community structure and ultimately ecosystem dynamics. To understand the functional roles of mycorrhizal plants and fungi, a trait-based approach (considering traits as any “measurable features of organisms related to their response to the environment and to other organisms”) can be used to go beyond taxonomy to understand function. For example, the frequency with which a plant species associates with mycorrhizal fungi (plant mycorrhizal status) is a plant trait that can indicate the prevalence and importance of the mycorrhizal association in a plant community or ecosystem. The aims of this PhD project is to: 1) determine the phylogenetic and environmental drivers of mycorrhizal status in the European flora; 2) compile and analyse information about the phylogenetic origin and ecology of plant species that are never colonized by mycorrhizal fungi; and 3) explore how mycorrhizal fungal communities differ between the roots of plants with contrasting mycorrhizal statuses, in different environmental conditions. Understanding how mycorrhizal traits and patterns of association in the symbiosis change along environmental gradients will help us to predict ecosystem function in future conditions. This project will also improve our understanding of fundamental issues related to the mycorrhizal symbiosis and its impacts on plant individuals and communities.