Research Fellow, Data Scientist for the ERC-funded Dissident Networks Project

Brno, Czech Republic
Friday, 26 March 2021
End of advertisement period
Friday, 30 April 2021
Contract Type
Fixed Term

Department Centre for the Digital Research of Religion – Faculty of Arts
Deadline 30 Apr 2021
Start date 1 September 2021 (negotiable)


Dean of the Faculty of Arts, Masaryk University announces an open competition for:

Full-time (part-time negotiable) research fellowship for a data scientist in an ERC-funded research project in computational history and social science

Department: Centre for the Digital Research of Religion, Department for the Study of Religions, Faculty of Arts, Masaryk University

Position: Researcher

Work time: 100% (part time is negotiable within the hiring process)

Number of open positions: 1

Expected start: 1 September 2021 (negotiable)

Duration: 31 August 2022 (first contract), 31 August 2026 (very probable extension based on performance review)

Deadline for applications: 30 April 2021 23:59 CET (UTC+1)

The Dissident Networks Project (DISSINET,, principal investigator Dr. David Zbíral) - an ERC Consolidator Grant-funded research initiative based at Masaryk University (Brno, Czech Republic) - offers a fellowship for a data scientist. The successful applicant will participate as a fully-fledged research fellow in an interdisciplinary research project between computing, social science, and the humanities which studies the social, spatial, and discursive patterns of medieval dissidence and inquisition through various computational approaches including social network analysis, geospatial data analysis, and natural language processing. The team will include a specialist in each of those fields. Historians in the team will work on transforming premodern sources into rich structured data on human interactions in dissident religious cultures of the past and on inquisitorial trials. The target volume of manually collected data is ca. 20,000 persons, 5,000 locations, 200,000 richly structured statements, and 2,000,000+ individual data points. Another extensive layer of data will be provided by natural language processing.

Rather than a specialist in a narrow field of scientific computing or data analysis, the successful candidate will be a mixed-profile, creative data scientist receptive to approaches in the social sciences and the humanities and previous research experience. They will participate in the team’s research, contribute to its research agenda and publications, and bring in strong competence and creativity in data science, scientific computing, and data management. The ERC-funded position will provide the successful candidate with the opportunity to produce mixed-methodology work and build a truly cutting-edge research profile.

The position is residential (although with reasonable flexibility for the duration of the pandemic). Brno is a very pleasant university city ca. 2 hours by direct train connection from Vienna and Prague, offers all the opportunities of a modern metropolis, and has very favourable living costs.


  • M.A., MSc. or Ph.D. degree in a relevant field (e.g. a computer scientist with experience of or interest in modelling in social sciences / humanities, a social scientist / humanities scholar with deep practical experience of the relevant technologies).
  • Interdisciplinary creativity, interest in computational social science.
  • Strong background in scientific computing (esp. Python, R) and data transformations.
  • Understanding of the importance of good practices for producing reliable software and reproducible analyses (e.g. version control, issue tracking, automated testing, package management, literate analysis tools such as Jupyter and R Markdown).
  • Experience in knowledge representation (esp. graph databases, RDF).
  • Solid skills in database management and query languages.
  • Organizational competences (coordination of external programmers).
  • Experience in research and academic writing.
  • English language (C1 or higher).

Other qualifications of interest to the project:

  • Ph.D. degree or Ph.D. studies approaching completion.
  • Experience of working in an interdisciplinary team.
  • Server administration (UNIX).
  • Cloud computing, parallelization of code.
  • Understanding of methods of interest in the project (esp. natural language processing, social network analysis, GIS, agent-based modelling).
  • Experience of visually presenting research outcomes.

We do not expect candidates to possess all of these “other qualifications of interest”, and recognise there may be other qualifications beyond this list that could enhance DISSINET’s research profile.

We offer:

  • Creative work across disciplines in an exciting and career-enhancing frontier-research project and in a new and little explored area of data science.
  • Growth in interdisciplinary research.
  • Competitive salary commensurate with an ERC-funded project.
  • Individual research budget for participating in conferences and workshops, choosing books and software to be purchased, etc. (ca. 4,000 € each year for a full-time research fellow).
  • Participation in writing high-profile publications in computational social science, SNA, history, historical GIS, and the digital humanities.
  • Friendly and informal working environment.


  • Participation in data science research in history (data transformation, analysis, visualization, management).
  • Managing the DISSINET database (understanding the data model and designing its further developments, describing and presenting it, creating elements of automation, compiling queries on demand, training team members in the query language, bringing DISSINET data model in line with existing standards and enhancing its interoperability).
  • Creating and setting tools for data processing.
  • Supervising external programmers and database specialists, translating between them and the team.
  • Co-authoring articles (incl. as lead author).
  • Participating in the team’s discussions, meetings, tutorials, and other activities.
  • Managing the project’s website.
  • Contributing to the project’s visibility (papers at conferences, publications, online outcomes, social media).
  • Contributing to the project’s annotated bibliography.

If the applicant would prefer a part-time position, the extent of these responsibilities will be negotiated within the hiring process.

Attachments to the application:

  • Letter of motivation (in English). Within the candidate’s description of what they will bring to the project, they should provide an initial description of how they would approach the data science aspect of DISSINET based on their reading of this call and the DISSINET website.
  • Letter of recommendation, e.g. from the leader of a research team in which the candidate was involved (candidates may either submit their referee’s letter themselves or, if preferable, ask their referee to send it to the PI confidentially).
  • Structured CV (in English) with an overview of competences, language skills, research experience, and a list of publications (incl. submitted).
  • Two examples of code for research use (co-)authored by the candidate (e.g. data transformation and analysis scripts in Python or R), with comments in the code and/or documentation (if co-authored, also with a description of the candidate’s contribution).
  • Up to two examples of academic texts (co-)authored by the applicant (if co-authored, with a description of the candidate’s contribution).
  • Scanned proof of the applicant’s highest university degree.
  • Optionally (for Ph.D. candidates approaching the completion of studies) written proof of thesis submission or progress in studies.

The first round of the selection procedure will be based on the submitted attachments. In the next phase, the short-listed applicants will discuss with the PI their possible involvement in the DISSINET project, develop their take on the DISSINET research agenda from the perspective of data science (in writing, 1,000 to 2,000 words; the shortlisted candidates will receive further details), and participate in an interview with the selection committee, presided over by the PI, via videoconference.

The candidate’s degree does not need to be recent for this position. Career breaks do not pose any problem: we are very open to those seeking to return to academia, provided their skills and interests are suited to the role. Applications from female candidates are particularly encouraged.

How to apply...?

Application with all required documents should be sent by e-application available below. Electronic application deadline is: April 30, 2021.