Below information is prepared for students interested in applying for the PhD programme in Information Society Technologies at the School of Digital Technologies at Tallinn University.

What to do and whom to contact

The admission process involves two parallel processes that need to be followed. It is important that you start early with both these processes because both take some time.  

  1. The general admission process that is dealt with by the central admission unit at Tallinn University:

  • Extensive information on what the formal requirements are, what to submit for the application and about deadlines can be found on the general information page of the PhD program. Here you can also find details about the curriculum.

  • In case you have any questions about any of this, including also language requirements, visa requirements and where to send the application should be directed to:

  1. Finding a research topic and a supervisor is dealt with by the School of Digital Technologies.

  • When you apply for a PhD, you will be required to submit a research proposal together with an agreement by a potential supervisor. Below you find information about this process.  


Finding a topic and a supervisor

Current admission is open for project-based research (4) and open topics (2). 


Research Topics at the School of Digital Technologies

The School of Digital Technologies is offering four project-based research topics for PhD students. Information can be found below:

Computer Science Education
Public engagement services with open cultural data
User modelling and user-adapted interaction
Learning at Workplace in the school-industry partnership for Digital Transformation


The following recording and materials also contain presentations of these areas and the topics they offer.

You can use this Template to write your Research Proposal.


Computer Science Education

Contact: Mart Laanpere (

Computer Science Education has become a political priority in Estonia since 2017, informatics curricula for basic schools and gymnasiums have been recently updated and equipped with up-to-date digital textbooks and other learning resources. The main issue that still remains is serious lack of qualified teachers who are able to teach these new courses.

In 2018, HITSA and IT Academy granted a significant financial support to Tallinn University to re-open and update the masters program "Informatics teacher, school ICT manager" that has been closed since 2016 due to low enrollment numbers. Any university that is dedicated to deliver and develop a masters program should guarantee the research-based foundation for this field of study, and DTI has lacked high level research in the field of Computer Science Education (CSE).

Herewith, DTI is applying for a PhD position that would allow to increase the research and teaching capacity of DTI in the field of CSE. The research topic should be related to the current needs of schools and teachers in Estonian context, and on the other hand, also to match the recent trends in CSE research community. Such topic could be, for instance, pedagogy-driven design of digital learning environment for Computer Science Education. 

Research Areas and Possible Topics

Online learning platforms and interactive learning resources, and the large-scale data streams that they generate, have the potential to transform education as well as our scientific understanding of learning. Computer Science Education (CSE) researchers are increasingly making use of large collections of data generated by the click streams coming from eTextbooks, interactive programming environments, and other smart content. However, CSE research faces barriers that slow progress:

  • Collection of computer science learning process and outcome data generated by one system is not compatible with that from other systems; 
  • Computer science problem solving and learning (e.g., open-ended coding solutions to complex problems) is quite different from the type of data that mainstream learning analytics focuses on; 
  • Digital learning resources, tools and platforms used in CSE are often not designed with pedagogy in mind. 

One of these prioritised research topics should be addressed by envisaged PhD research. In the future perspective, there is a need for a full-time senior lecturer (a PhD holder who is also active in CSE research) who would teach the core subjects in the informatics teacher education program, to guarantee the high academic level of the program.


Public engagement services with open cultural data

Contact: David Lamas (, Kai Pata (, Sirje Virkus (

This PhD position calls for exploring the issues of curating cultural data to enhance its usability in new public services; designing and testing out the services based on open cultural data; developing the algorithms to process cultural data for specific services needs such as for creating awareness, enabling crowd collaboration and engagement based on aggregated dynamic open data.

The government bodies, as well as supervised public bodies, are going to publish as open data the cultural data that falls within the definitions of public information. ‘Open cultural data’ is data from cultural institutions that is made available for use in a machine-readable format under an open licence ( e.g. language data, media data, cultural heritage data, literature data corpora). Open data is a new digital commons, a resource to which citizens are entitled and that must be delivered qualitatively. These data sets are provided for re-use by citizens, academic institutes and enterprises in order to contribute to the development of the national cultural product. It is envisioned that open data could be creatively repurposed, aggregated or augmented with other data sources in the context of evolving data infrastructures which are attuned to the specific needs and interests of civil society actors. Open cultural data supports discovery, reuse and innovation in digital humanities.

By generating transparency, open cultural data can feed civic agency such as social mobilisation, informed decision-making and behavioural change increasing wellbeing and sustainable actions based on feedback loops from dynamic data. New potential services that use open data may promote data driven engagement of the crowds for empowering citizens, and solving public problems. For example open city spaces may be made smart, by enabling decision-making, engagement and interaction opportunities in shared spaces fuelled by open cultural data.



User modelling and user-adapted interaction

Contact: David Lamas (, Aleksander Väljamäe (

Personalization techniques, in general, build upon user models. These models are application specific and account both for long term user properties (e.g. preferences, attitudes, personality traits, which are stable over longer time periods) and short term User properties (e.g. affective/cognitive states, which can change more rapidly). Long term properties can be acquired with existing acquisition techniques using either one-time Intrusive questionnaires or slowly and unobtrusively via various modalities, e.g. ratings, browsing history, social media streams. However, these approaches fail for short term Properties, which change rapidly. Hence, personalization techniques still lack quick, responsive and unobtrusive techniques to acquire the short term user properties.

The measurement of peripheral physiology and brain responses of users can complement the traditional user feedback acquisition techniques by providing more insight into short term changes of the user. Physiological measurement can be continuously available, quantitative and relatively unobtrusive. Therefore, personalized systems can now aim for a more detailed and temporally adaptive user models that try to mimic the dynamics of the user’s cognitive and affective states. In addition, the physiological data can also be used for complementing long-term user properties (e.g. personality traits). Furthermore, physiological measures can be combined with behavioural data to provide a more detailed multimodal model of the user.

Research Areas and PhD Topics

PhD studies will concentrate on the research embracing:  

  • Development of physiological user models for personalized systems
  • Collection of datasets with physiology information in personalized systems/human-computer interaction
  • Enhancing user/learner models with physiology;
  • Evaluation of physiology-based personalized services;
  • Design, development and validation of novel applications considering physiology including games, cinema, theatre, multimedia content, and social media.


Learning at Workplace in the school-industry partnership for Digital Transformation

Contact: Tobias Ley (, Kairit Tammets (

Keywords: digital transformation, workplace learning, vocational education

In order to sustain growth in the conditions of aging population, lack of skilled labour and rapid technological development, the Estonian economy needs workforce with interdisciplinary skills who has both good vocational and ICT skills (Kutsekoda, 2018). Such workforce would enable the Estonian companies and institutions to fulfill the potential of ‘ICT horizontally through other sectors’—one of the growth areas of the Estonian smart specialisation strategy (Estonian Development Fund, 2013)—and start or proceed in their digital transformation.
Learning, especially workplace learning, and digital transformation go hand in hand. Digitally maturing organisations have to be capable to adapt to changes fast and thus, provide their employees with diverse learning opportunities to ensure that they have the skills necessary to take advantage of technological developments (Kane et al. 2015). Therefore, it would be reasonable to develop vocational students’ skills and habits of workplace learning during their traineeships, which are often the first encounter with an authentic work environment in their to-be-profession. Moreover, as digitally maturing organisations increasingly provide web-based and just-in-time learning (Kane et al. 2015), then the students should also learn to learn with technology as well as about technology.

Research Goal and Research Questions

The aim of the proposed research is to propose novel mechanisms to support workplace learning in collaboration with the vocational schools and companies to prepare the students for digital transformation at their future workplaces.

  • What are the skills/knowledge required from vocational school students to cope with and contribute to digital transformation of workplaces?
  • To what extent are vocational school students prepared for using digital technologies for workplace learning, to adapt to the changing needs of a digital transformation process?
  • What are the technology-mediated services and practices to supporting vocational school students to be ready for digital transformation at their future workplaces.

Addition to described project-based research topics, other topics related to digital technologies are in focus through open competition. These topics are aligned with the priority research fields of the School of Digital Technologies: Digital transformation and lifelong learning and topics from the fields of technology-enhanced learning, information sciences, mathematics and human-computer interaction. To align PhD research plan with the priorities of the school, it is very important that you will find possible supervisor and plan your research proposal in close interaction with a supervisor at the school. It is therefore important that you start early and plan for several iterations of your research proposal until it is in a state that it can be submitted. Depending on your own availability and the availability of your supervisor, this process takes at least one month, sometimes more. 

The following recording and materials also contain presentations of these areas and the topics they offer. You can use this Template to write your Research Proposal.

Open Research Topics at the School of Digital Technologies

Even for applying with an open topic, its is critical that your topic is aligned with one of the ongoing or future research projects. This is because most of our research students are financed through these projects. This alignment happens in close interaction with a supervisor at the school. It is therefore important that you start early and plan for several iterations of your research proposal until it is in a state that it can be submitted. Depending on your own availability and the availability of your supervisor, this process takes at least one month, sometimes more.  

To define the topic and find a supervisor follow the following steps: 

  1. Read the information on this page carefully
  2. Try to identify a research topic or a research area that your research interest is aligned to 
  3. Prepare a short (2-3 page) description of your initial research idea 
  4. Send your description to the head of the IST curriculum Prof. Tobias Ley ( and he will try to identify a prospective supervisor. Of course, you can also contact a supervisor directly.  

Once a supervisor has agreed to help you prepare the research proposal, continue with her or him.