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 the next possible date our Department Knowledge Technologies for the Social Sciences (KTS), Team FAIR Data located in Cologne, is looking for a
Postdoc / Senior Researcher
Information Retrieval, NLP, Knowledge Graphs
(Salary group 13 TV-L, working time 80%, currently limited to September 2026)
The department Knowledge Technologies for Social Sciences (KTS) conducts research at the intersection of information retrieval, knowledge graphs, human information interaction and machine learning 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.
In the context of the consortia NFDI4DataScience and BERD@NFDI of the National Research Data Infrastructure (NFDI) KTS develops innovative services with the goal to improve the search for and the reusability of research data for data science and artificial intelligence.
Your tasks will be:
- Research in the areas of information retrieval, natural language processing, knowledge graphs and/or machine learning, with a particular focus on research data
- Conceptual design, modeling and implementation of research-based services for the search for and the extraction and linking of data and their integration into knowledge graphs
- Engagement with and coordination of partners in the NFDI, supervision of doctoral students, exchange with relevant communities (e.g. EOSC)
- Dissemination of project results through publications and workshops
Your profile:
- Scientific university degree (diploma/master) and PhD in Computer Science, Data Science or comparable fields
- Good expertise in the areas of information retrieval, semantic technologies, knowledge extraction, NLP and/or knowledge graphs
- Solid experience in software development with Java, Python, Elasticsearch, Web and/or DB technologies
- Project management experience desirable
- Good oral and written communication skills in English, knowledge of German desirable
Our Benefits:
- A fast growing and international working environment with a lot of creative scientific freedom
- Excellent career opportunities in research as well as in software development and data engineering
- Flexible working hours and the possibility of up to 60% mobile working within Germany
- 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
For further information concerning the tasks, please contact Peter Mutschke via phone +49 (0221) 47694 - 500 or 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 19.12.2024.
Our reference number is: KTS-66
GESIS offers an exciting work environment for interdisciplinary research at the interface between social sciences and computer sciences. As an infrastructure institution, we serve the promotion of the social science research, and we are in close cooperation with well-known international research institutes.
GESIS supports your career developments. We offer a wide range of career possibilities within an attractive working atmosphere with a high level of self-responsibility and scope for action. You work in an international environment in the heart of Cologne and you benefit from our flexible working area.
GESIS guarantees the attention of the disability regulations and advances the professional gender equality.
As a family-friendly employer, we are certified by the audit Work&Family since 2010.
Here you will find further information.
