Computational Social Science Jobs

description 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 as soon as possible our Department Computational Social Science (CSS) , Team Transparent Social Analytics located in  Cologne , is looking for a Student Research Assistant (15,20 € / 16,09 € hourly rate, 14 hrs./week, temporary) 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 goal of the Transparent Social Analytics team is to make methods for data collection, preprocessing, and analysis of digital behavioral data accessible and transparent, and to make computational social science research reproducible. The successful candidate will, in particular, support the team around the  GESIS Methods Hub in designing, testing, and evaluating AI applications. Your tasks will be: Creating analysis scripts for social science research questions using R or Python Generating and testing synthetic data that replicates properties of social science or digital behavioral research using AI models Checking statistical analyses for reproducibility Your profile: Completed (or soon to be completed) Bachelor’s degree in computer science or a related field Experience in programming with R and Python Interest in and experience with generative AI and Large Language Models Good command of English or German Our Benefits: Opportunity to actively contribute to systems used by many researchers Possibility to participate in scientific work and publications Flexible working hours and regulations for mobile working Very good conditions for reconciling work and family life Holistic company health management and discounted participation in the university's sports programme  Promotion of your skills through further training measures Contact For further information concerning the tasks please contact Dr. Christina Viehmann via  E-Mail . If you have questions about the application process, please contact Franca Tosetti via  E-Mail . Interested? Please apply via our Online-application portal until  06.08.2026 . Our reference number is: CSS-SHK-38