Academic Competition

Tallinn University has announced a public competition for the position of Professor of Information and Data Science. The elected candidate commences work on the first career level of the position (associate professor) with the aim of supporting their development into a leader of the relevant study and research field in Tallinn University, and moves to the second career level of the position (professor) by way of evaluation. The position will be filled from 01.01.2023. The start of the employment contract is flexible and will be negotiated with the winner of the competition (the elected professor).  

The deadline of submitting the application documents is 5th September 2022 (incl).

Title of the position: Associate Professor of Information and Data Science (career level I of Tenure Track Professorship)
Academic unit: School of Digital Technologies
Study area: the position belongs to the current study area of Information Sciences

Description of the academic work field
The professor is expected to focus his/her teaching, research and outreach on information and data sciences, having competences in both fields (information science and data science), with as one of the objectives to raise the capability of public sector institutions (e.g. libraries, museums, archives, government institutions, health organizations) for efficient information and data management. The professor will also lead the development of tools for data informed decision making.

School context
Information Sciences is currently one of the study areas of the School of Digital Technologies. Other academic areas of the school are: Applied Informatics; Human-Computer Interaction; Mathematics and Didactics of  Mathematics; Technology Enhanced Learning. The focus of the research and teaching in the study area of information sciences is currently based on the development of digital libraries, information and knowledge management, information, media and digital literacy, management of digital cultural heritage, electronic document and record management and electronic publishing. The study area of information sciences currently offers a bachelor’s programme on Information Science, master programme in Information Science, and is part of the Technology Enhanced Learning MA, Open Society Technologies MA and Information Society Technologies PhD programme. Further cross-school developments include a joint focus on cultural data analytics with the  Baltic Film, Media and Arts School (BFM) and the School of Humanities (HUM) in the ERA Chair of Cultural Data Analytics (CUDAN), which provide shared research and teaching opportunities in information and data science.

The strategic importance of the position
The relevance of the field to the development priorities of TLU, Estonia and Europe: Information and data are the most important enabling factor of contemporary information society. A number of international (such as A European Strategy for Data or LIBER strategy 2018-2022) and national strategies have made access to data and information, and efficient information management as a key factor in the sustainable economic, political and social development; without relevant information it is impossible to function effectively as an individual, as an organization or as a society. Since 2014, the European Commission (EC) has taken a number of steps to facilitate the development of a data-agile economy. The strategy for “Europe Fit for the Digital Age” (2020) includes European Data Strategy which aims to make the EU a leader in a data-driven society. The Commission has proposed a “Regulation on European Data Governance” (2020) as part of its data strategy. This Regulation will play a vital role in ensuring the EU’s leadership in the global data economy. In Estonia, „Green Paper on the Organisation of Public Services“ by the Ministry of Economic Affairs and Communications of Republic of Estonia (approved by the Government in 2013) outlines the need to move from records management to holistic information management. Based on this, the Estonian Information Society Development Plan 2020 also set the priority of implementing information management in the public sector. In October 2021, the government submitted the Development Plan for the Estonian Digital Society for the period up to 2030 for approval to the Estonian Parliament. The document emphasizes the need to increase the quality and level of information and data management and related competencies. Information and data management supports smarter governance and would help to cope with the various information channels and flows. One of the most important directions in this document that allows for a leap forward and ensures the sustainability of the digital state is data-driven government and data management that are directly linked with information and data science. It is foreseen to raise the capability of public sector institutions by using data analytics, including upgrading the relevant awareness and skills in information and data management and creating and providing a legal space and the necessary tools for information management. In addition, information portals that provide simple and secure access for data and information, information services for users and productive use of the information generated in different channels are highlighted. Thus, the role of effective data and information management in the contemporary society is utmost important. According to the Development Plan for 2020-2022 of the Tallinn University, TLU contributes to the development of innovative information society solutions and the introduction of digital media culture of different life areas. Important components of the digital media culture are the information-related competencies (data, information, media and digital literacy). Therefore, the development plan highlights the development of digital literacy and media related competencies. The professorship in information and data science will explicitly contribute to the area of information culture and will be linked to the digital and media culture focus field of the university.

Current strengths of TLU in the field of the position: The origins of the information science at TLU can be traced back to 1965, when a first degree programme was established. Study programmes in information science are taught only at Tallinn University in Estonia. According to the international assessment of study programmes in information sciences in 2017, TLU has sufficient research/teaching capacity in information sciences.
 

The strategic importance of the position within the school and how it relates to the other planned tenure and non-tenure positions (i.e. how they complement each other, etc.): Although there are several professorships in data science at other universities in Estonia (at the University of Tartu and TalTech), there are no combined professorships in information and data science. Within the School of Digital Technologies of Tallinn University, due to the interdisciplinary nature, the position is closely linked with all other study areas. For example, the study area of technology-enhanced learning will benefit from the research that aims to support the culture of data-informed decision making in education and advancement of new research methods based on data mining, machine learning and ontology engineering. The challenges in scale and heterogeneity of data also fundamentally change how users interact with data and information, how the data and information is visualized, what algorithms are needed to support understanding and interpretation of the results of data science models, how decisions are made, and how user feedback is acquired and incorporated – therefore, the study area of human-computer interaction will need to be tightly integrated with data science models. From the study area of applied informatics point of view, very large data volumes, very high data rates, and very large numbers of users, demand new systems and new algorithms. New system architectures that can accommodate the heterogeneity and irregular structure in data access and communication are needed. Mathematics is very important in the field of data science as concepts within mathematics aid in identifying patterns and assist in creating algorithms. The understanding of various notions of statistics and probability theory are key for the implementation of such algorithms in data science. The professorship will be closely linked with the research group of Digital Transformation as intelligent information management is a crucial part of digital transformation. However, due to the specific focus of the professorship on information and data science, there is no overlap between the scope of other tenure positions. The professorship in information and data science will explicitly contribute to the area of information and data culture and will be linked with the digital and media culture focus field of the university.  

Requirements for the candidate
Candidates for the tenure system position shall meet at least the requirements of career level I of tenure system professor (associate professor), which are stipulated in Annex 2 and respectively in Annex 9 and 10 to the Employment Relations Rules, incl.:

• The candidate must have a doctoral degree or equivalent qualification;
• If the candidate has worked as a professor for at least five years immediately prior to applying for the position of a professor at the University, at least one doctoral thesis must have been defended under their (co)supervision during the last five years. 

Academic activity requirements 

• he candidate must have a strong research and publication track record and possess considerable demonstrable knowledge in the field of information science and data science;
• experience in coordinating research projects and in organising international conferences and workshops;
• demonstrate capacity to generate external national or international funding for research; 
• active membership in international professional and/or research organisations, expert groups, journal editorial boards, programme committees of international conferences;
• substantial pedagogical experience in teaching and supervising;
• experience in organising societal outreach activities;
• experience in developing and running international curricula;
• the candidate is expected to have leadership experience and demonstrate competence in this area.

Language skills:

• English on the level necessary for conducting teaching and research work;
• An employee who does not speak Estonian is expected to start acquiring proficiency in Estonian upon starting work and achieve language proficiency level B1 within three years and a level comparable to level B2 within five years in order to be able to perform tasks related to institutional development and administrative work in Estonian.

Job responsibilities
General work duties are determined in Annexes 1, 2 and 10 of the Employment Relations Rules of Tallinn University. The duties are approximately divided as follows: 1) Research and development activity – 55%, 2) Teaching activity – 30%, 3) Social and institutional activity – 15%.
 

Specific tasks:

• contribute to the development of other academic areas of the School of Digital Technologies and other schools of the university in the fields of information and data sciences;
• run a regular research seminar in information and data sciences;
• contribute to the sustainability of the research group in information and data sciences (including applying for international research grants).

Working load: 1,0 (40 hours a week).
Remuneration: In accordance with TLU Remuneration Regulation and by negotiations with the director of the School of Digital Technologies.
In addition to remuneration, a limited allowance is foreseen to the tenure professor, which can be used to cover the costs of research and development expenditure, members of the research team etc. related to the position.
Location: Professor is expected to live in Tallinn and work at the premises of Tallinn University.
Start of the employment: The position will be filled from 01.01.2023. The start of the employment contract is flexible and will be negotiated with the winner of the competition (the elected professor).