Geospatial Data Analyst for the ERC-funded Dissident Networks Project
Dean of the Faculty of Arts, Masaryk University announces an open competition for:
Full-time research fellowship for a geospatial data analyst in an ERC-funded research project in computational history
Department: Centre for the Digital Research of Religion, Department for the Study of Religions, Faculty of Arts, Masaryk University
Work time: 100%
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, https://dissinet.cz/, principal investigator Dr. David Zbíral) - an ERC Consolidator Grant-funded research initiative based at Masaryk University (Brno, Czech Republic) - offers a full-time research fellowship in geospatial data analysis / GIS. The successful applicant will participate in research concerning the spatial patterns of religious non-conformism and inquisitorial trials in medieval Europe, and develop interactive map applications, data visualizations, and GIS tools for the project.
The position has both a data analysis and visualization / scientific programming / application development component and an academic component (research on the basis of data collected by historians in the project and other available datasets, presenting at conferences, co-authoring publications, etc.). The ratio between the two is likely to change depending on the project’s needs in its different phases, and the general balance is partly negotiable in the selection process, depending on the candidate’s interests and competencies.
DISSINET at large focuses on various computational approaches to medieval Christian dissent and inquisition, also including social network analysis and natural language processing. The successful candidate will have the opportunity to produce mixed-methodology work in this collaborative context. The ERC-funded position thus represents a unique opportunity to build a truly cutting-edge research profile.
The position is residential (although with reasonable flexibility for the duration of the pandemic).
- M.A. or Ph.D. degree in geography, GIS or a similar field.
- Knowledge of geospatial data analysis (e.g., R, Python, GDAL) and geostatistics.
- Experience with spatial / spatiotemporal / complex data visualization, ability to work with standard tools and languages for spatial data visualization (e.g., QGIS, D3, Leaflet, GeoPandas, R).
- Experience with web programming.
- Expertise in map design and the basics of cartography.
- Interest in historical research and complex spatiotemporal and social data.
- Competence in academic writing and willingness to contribute text to co-authored publications.
- English language (C1 or higher).
Other qualifications of interest to the project:
- Ph.D. degree or Ph.D. studies approaching completion.
- Experience in research-oriented GIS.
- Experience of working in an interdisciplinary team.
- Previous participation in a humanities or social sciences project.
- Experience with databases and query languages (the project’s concept is based on graph databases).
- Data standards and interoperability (e.g., RDF).
- Version control (e.g., GitHub, GitLab).
- Experience with geocoding.
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.
- Freedom to pursue your intellectual interests and to work creatively across disciplines in an exciting frontier-research project.
- 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).
- Participation in writing high-profile publications in historical GIS, digital humanities, history, computational social science, and network analysis.
- Friendly and informal working environment.
- Performing geospatial analyses of historical datasets.
- Creating maps and other visualizations of data (spatial and beyond).
- Participating in the development of the project’s software tools.
- Co-authoring articles (incl. as lead author).
- Participating in the team’s discussions, meetings, tutorials, and other activities.
- Contributing to the project’s visibility (papers at conferences, publications, online outcomes, social media, etc.).
- Reading and summarizing literature, contributing to the project’s annotated bibliography in Zotero.
- Organizational and administrative responsibilities related to the project.
Attachments to the application:
- Letter of motivation (in English) stating your past experience in relation to the list of skills above.
- Two letters of recommendation from scholars in a relevant field (candidates may either submit their referees’ letter themselves or, if preferable, ask their referees to send them to the PI confidentially).
- Structured CV (in English) with an overview of competences, programming skills, language skills, research experience, and a list of publications (incl. submitted).
- Two to four examples of maps or (spatial) data visualizations (preferably in the interactive form, ideally a link to a version deployed online) (co-)authored by the applicant (if co-authored, with a description of the candidate’s contribution).
- Up to two examples of academic texts (co-)authored by the applicant (in any European language; if co-authored, with a description of the candidate’s contribution).
- Scanned proofs of the M.A. and/or Ph.D. degree (e.g. academic transcript, certificate).
- 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 receive geocoded data and will demonstrate their skills and approaches to data analysis and research by processing the data and submitting an online outcome with a short description; after submitting this task, they will discuss with the PI their possible focus within the larger DISSINET project 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.