Load: 1,0 The duties are approximately divided in (1) research (90%), (2) teaching (5%) and (3) internal and external service (5%).
Salary: to be agreed, but internationally competitive.
Location: Tallinn, Estonia.
Language skills: English C1,  Estonian is not required; if staying longer in Estonia, the candidate would need to acquire Estonian as a working language within 3 years in order to be able to participate in administrative tasks.

Tallinn University has announced an open competition for five positions of Research Fellow in Cultural Data Analytics in H2020 funded ERA Chair project CUDAN to commence as follows: 

2 positions in Baltic Film, Media, Arts and Communication School;
2 positions in the School of Humanities
1 position in the School of Digital Technologies 

Start of the employment contract is negotiable: between 15.06.2020- 01.09.2020.
The duration of the contract is up to 3,5 years. 

Funded through the European Commission, the designated CUDAN ERA Chair holder, Professor Maximilian Schich, together with the CUDAN project team, the Baltic Film, Media, Arts and Communication School, the School of Humanities, and the School of Digital Technologies at Tallinn University, is looking for research fellows in the area of Cultural Data Analytics to deepen our understanding of the nature of cultural interaction, cultural dynamics, and cultural evolution, doing research while nurturing multidisciplinary cross-fertilization. Through this recruiting, the CUDAN project will bring together a group of at least 5 research fellows and 5 PhD students to harness the rare high-risk/high-gain opportunity of combining multidisciplinary science, computation, information design, with art and cultural history, cultural media studies, and cultural semiotics, in close collaboration and co-authorship. The newly established research group will form the core of the CUDAN Open Lab, which in addition to research aims to function as a forum for intellectual exchange, and as an incubator for follow-up projects. Ideally, the research fellows contribute aspects of network science, complexity science, science of science, computational social science, machine learning/AI, information science, data science, data visualization, user experience design, and/or digital humanities to the locally existing expertise in art and cultural history, cultural media studies, cultural semiotics, and digital technology. Beyond the local environment, the CUDAN initiative will also provide the research fellows and PhD students with the opportunity to work closely with high-profile external partners in multidisciplinary science, cultural heritage institutions, and stakeholders in the cultural industries in Estonia, in Europe, and around the globe. More information on the CUDAN project, see here.

We are particularly interested to work on the following research challenges:

• Using machine learning to analyze images and/or audio-visual material over historical time scales, to reveal patterns and biases in large data collections through a kind of “artificial neural science”.

• Using linguistic topic modelling and/or bi-partite network science to analyze the structure and evolution of large corpora of texts and/or classifications, feeding into a “palaeontology of memes”.

• Using temporal multilayer network analysis and/or topological data analysis to make sense of large cultural knowledge graphs, through capturing fundamental emerging patterns of “network multiplicity”.

• Combining the analysis of multimedia, unstructured, and structured data in a so-called embed-everything-approach that could result in a kind of “multidimensional fluid-dynamics of meaning”.

In addition, we aim to nurture the Cultural Analytics community through addressing the following challenges:

• Mapping and characterizing the achievements, opportunities, and limits of Cultural Data Analytics, ideally resulting in actionable maps of the relevant “multidisciplinary ski area”.

• Enabling and optimizing the CUDAN Open Lab experience through a conscious effort of user experience design, observing and designing workflows, events, and other forms of intentional “academic mixing”.

Candidates that are motivated and have the capacity to spearhead one of these aspects are strongly encouraged to apply!

Requirements for the candidate (incl. professional experience)
Candidates for the research fellow position shall meet the requirements of career level II of research fellow (Annex 5, 9 and 10 of TLU's Employment Relations Rules). 

• The ideal candidate has a PhD in a field closely related to Cultural Data Analytics, with expertise in quantification, computation, and/or visualization, ideally including previous working experience with large-scale socio-cultural data.

• The individual focus could be in machine learning/AI, network science, topological data analysis, complexity science, science of science, computational social science, information science, data visualization, user experience design, and/or digital humanities.

• Candidates with a PhD in a seemingly unrelated field whose methods could nevertheless be valuable to the CUDAN project will be considered: Examples include experts in socio-physics, computer vision, species niche modeling, time-series analysis, or matrix clustering as found in systems biology and neuroscience.

• The working language of the CUDAN research group is English.

Job responsibilities

• Performing research in co-authorship with CUDAN research group members and external partners under the supervision of the CUDAN ERA Chair holder, with typical activities including research design, data acquisition, data preparation, data analysis, visualization, and the composition of figures and manuscripts.

• Publishing and assessing research results, ideally aiming for high-profile multidisciplinary journals and conferences.

• Participation in CUDAN Open Lab activities, including discussions with students, faculty, and external stakeholders, mutually building and sharing expertise, developing novel research ideas, and supporting the application for additional funding.

• Co-supervising and teaching CUDAN students.

• Openness and readiness to engage in multidisciplinary translation, within a diverse and international research group.

Required application documents

The candidates are expected to submit the required applications documents (preferably in PDF-format) by the March 16th 31st 2020 to Personnel Office of Tallinn University (Narva mnt 25, room T-218, 10120, Tallinn, or digitally signed to konkurss@tlu.ee) with the title “Academic competition”:

• a signed application-motivation letter addressed to the Rector, which contains an overview of the candidate’s objectives in carrying out study and research and development or creative activities;

• a curriculum vitae, which shall include, among others, an overview of the candidate's teaching, research and development or other creative activity, and social and institutional activity;

• copies of a document certifying the qualification required from the position, and its annexes. The University shall have the right to request that the candidate submit the original or certified copies of the document certifying the qualification and its annexes. If higher education has been obtained abroad, the University shall have the right to request that the candidate submit the evaluation of the Estonian ENIC/NARIC concerning the conformity of the candidate’s qualification with the requirements established for the position;

• a brief statement of research experience and interests;

• a list of research publications, separately highlighting research papers published in internationally distributed publications peer reviewed by an editorial board;

• a link to or, if that is impossible, a file with the full text of one representative research publication;

• two letters of recommendation sent separately by the writers to konkurss@tlu.ee, with the title "CUDAN";

• documents and materials to certify other knowledge and skills, if the candidate considers these important.

Additional information: please refer your administrative questions to konkurss@tlu.ee and questions on content to project coordinator for CUDAN Mariliis Niinemägi, mariliis.niinemagi@tlu.ee