Postdoctoral Researcher in Computational Social Science: Research Infrastructures and Synthetic Social Media Data (CSS-119)

Postdoctoral Researcher in Computational Social Science: Research Infrastructures and Synthetic Social Media Data

(Salary group 13 TV-L, working time 75% GESIS, 25% CAIS; limited until 30.04.2029)

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 “SynDIKAT – Synthetic Disinformation Data, Infrastructure for Collaboration, and Analysis Toolbox for Social Media Research”, funded by the German Federal Ministry of Research, Technology and Space (BMFTR). The project is conducted jointly by the University of Münster, GESIS – Leibniz Institute for the Social Sciences, , and TU Dortmund University.

The position is jointly located at GESIS – Leibniz Institute for the Social Sciences (75% of the work time) within the Computational Social Science (CSS) department and at Center for Advanced Internet Studies (CAIS) (25 % of the work time).

• Development of research infrastructures for the sharing, documentation, and evaluation of social media datasets
• Design and implementation of APIs, data access mechanisms, and evaluation frameworks for open and synthetic datasets
• Research on synthetic data generation using Large Language Models and other generative AI approaches
• Evaluation of synthetic datasets with regard to realism, utility, privacy, and downstream task performance
• Development of benchmarking approaches for the evaluation of computational methods in social media and disinformation research

• Doctoral degree in Computational Social Science, Computer Science, Data Science, Information Systems, Computational Linguistics, Political Science, Communication Science, Sociology, or a related field
• Experience with machine learning and/or Large Language Models
• Experience with containerization technologies (e.g., Docker) and reproducible research workflows 
• Experience working with social media data, digital trace data, or other large-scale behavioral datasets
• Excellent programming skills in Python; experience with modern machine learning frameworks is desirable

• The opportunity to contribute to the development of next-generation research infrastructures for Computational Social Science
• An international, interdisciplinary, and highly collaborative research environment 
• Excellent opportunities to develop an independent research profile and establish international collaborations
• Flexible working hours and regulations for mobile working
• Very good conditions for reconciling work and family life, e.g. subsidies for childcare for children who have not yet attained the age of compulsory schooling
• Holistic company health management and discounted participation in the university's sports programme 
• Generous support for your pension provision as a direct insurance policy
• Promotion of your skills through further training measures