Postdoc in Social Data Science (CSS-126_intern)

GESIS – Leibniz-Institute for the Social Sciences is an internationally active research institute, funded by federal and state governments and member of the Leibniz Association.

Starting on January 1, 2027, our Department Computational Social Science (CSS), Team Data Science Methods, located in Cologne,

is looking for a

Postdoc in Social Data Science

(Salary group 13 TV-L, working time 100 %, limited until May 31, 2028)

The department Computational Social Science (CSS) collects digital behavioral data and provides computer-based methods for collecting and analyzing such data for social science research. It also supports scientists with the integration of digital behavioral data into their research designs. The department's research focuses on the quality of digital behavioral data, the development and validation of computational social science methods and the transformation of digital societies.

The position is part of the project “Developing AI-Powered Survey Infrastructures to Enhance Resilience Research” funded by the Leibniz Association, which we are conducting together with the Leibniz Institute for Resilience Research (LIR). The project aims to enhance survey data through the use of Large Language Models (LLMs) and digital behavioral data, with an application to resilience research.

• Coordination of the project within GESIS and with external project partners
• Leading the data collection of surveys and web tracking data (web browsing data) in collaboration with the GESIS Panel.dbd
• Application of LLMs, e.g., fine-tuning, application to survey data and web tracking data, and model validation
• Integration and statistical analysis of multidimensional data (web tracking data, surveys, LLM-generated measures)
• Publications with the principal investigators of the project

• University degree (M.Sc., Diploma) and a completed or well-advanced Doctoral degree in a field relevant for computational social science, such as applied computer science, political science, communication science, psychology, sociology, or related disciplines
• (First) Peer-reviewed publications
• Expertise in working with LLMs in the context of survey response simulations
• Excellent knowledge of quantitative data analysis in Python
• Excellent English skills in speaking and writing, knowledge of German is a plus

Contact

For further information concerning the tasks, please contact Prof. Claudia Wagner via E-Mail (claudia.wagner@gesis.org). If you have questions about the application process, please contact Christine Laßmann via E-Mail (christine.lassmann@gesis.org).

Interested?

Please apply via our Online-application portal until 20.10.2026.

Our reference number is: CSS-126intern