Senior Researcher & Team Leader (FAIR Research Data & Knowledge Graphs) (KTS-85)

GESIS – Leibniz Institute for the Social Sciences is an internationally active research institute, funded by the federal and state governments and a member of the Leibniz Association. Starting on January 1, 2027 , our Department Knowledge Technologies for the Social Sciences (KTS), Team FAIR Data located in Cologne , is looking for a Senior Researcher & Team Leader (FAIR Research Data & Knowledge Graphs) (Salary group 14 TV-L, working time 100%, initially limited to 4 years with permanent option) The department Knowledge Technologies for Social Sciences (KTS ) conducts research at the intersection of information retrieval, natural language processing, semantic technologies and human information interaction as foundation for innovative web portals and platforms for the search and use of research data. KTS innovations are based on a state-of-the-art software stack and research-based innovations in the aforementioned fields. For the FAIR Data team, we are seeking a Senior Researcher & Team Leader with experience in leading research projects and teams and an interest in further advancing the AI-readiness and FAIRness of research data—that is, its findability, accessibility, interoperability, and reusability. One focus of the team is the question of how research data can be harnessed for new forms of AI-supported scientific use with the help of technologies from fields such as natural language processing, information retrieval, and knowledge graphs. We are looking for a scholar with a proven track record who will further develop the team’s existing profile, contribute their own research priorities, and initiate new research and infrastructure projects. This position offers the opportunity to work at the intersection of basic research, applied research, and the development of sustainable research data infrastructures. Your tasks will be: Leading a research group that develops and investigates innovative methods and infrastructures for FAIRness and the AI-supported use of research data and metadata in the social sciences Collaborating with national and international research data infrastructure initiatives (in particular NFDI and EOSC), as well as other teams and departments at GESIS Leading research projects in areas such as natural language processing, information retrieval, knowledge graphs, and/or machine learning Securing competitive external funding Coordinating infrastructure activities of the team and the transfer of research findings into innovative research infrastructures Presenting research findings and infrastructure innovations at academic conferences and within interdisciplinary networks and communities Your profile: Completed academic university degree (Master’s or equivalent) and a completed or well-advanced doctoral degree / PhD in computer science or related fields Relevant scientific expertise in one or more of the following areas: natural language processing, information extraction, information retrieval, knowledge graphs, and machine learning Experience in managing projects and teams, as well as in securing and leading externally funded projects Excellent command of English (spoken and written); knowledge of German is a plus (we support and expect you to achieve C1-level proficiency in German within the first three years) Strong communication and problem-solving skills, as well as the ability to take initiative Our Benefits: A rapidly growing, international, and interdisciplinary work environment with close ties to regional and international research institutions in related fields Access to large research datasets, e.g., web and social media crawls 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 through a direct insurance plan Promotion of your skills through further training measures Contact For further information concerning the tasks, please contact Stefan Dietze via E-Mail ( stefan.dietze@gesis.org ). If you have questions about the application process, please contact Christine Laßmann via E-Mail ( christine.lassmann@gesis.org ). Interested? Then please apply via our online application portal until November 16 ,2026 . The reference number is: KTS-85