Research Associate Knowledge Graphs (KTS-75)

GESIS - Leibniz-Institut für Sozialwissenschaften; Köln; Vor Ort; EUR 50.000 - 60.000; Vollzeit

Zusammenfassung

A leading research institute in Cologne seeks a Research Associate for Knowledge Graphs to support the GRAPHIA project. The role requires a Master’s degree in Computer Science and skills in knowledge graphs, information extraction, and Python software development. Responsibilities include integrating data into the GRAPHIA knowledge graph, evaluating pipelines, and collaborative research. This position offers good career opportunities and is suitable for those interested in AI and social sciences.

Leistungen

International working environment

Excellent career opportunities

Flexible working hours

Subsidies for childcare

Company health management

Generous pension support

Further training opportunities

Qualifikationen

• Master's degree in Computer Science or related fields required.
• Research interests in knowledge graphs and AI are preferable.
• Expertise in Python and machine learning frameworks is important.

Aufgaben

• Implement approaches for integrating (meta‑)data into RDF for the GRAPHIA knowledge graph.
• Evaluate information extraction pipelines to identify mentions of entities.
• Collaborate on work packages in the GRAPHIA project.

Kenntnisse

Knowledge graphs

Information extraction

Machine learning

Artificial intelligence

Software development with Python

Database technologies

Search engine technologies

Semantic web technologies

Docker

Fluent English

Ausbildung

Master's degree in Computer Science or related fields

Jobbeschreibung

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 Information Extraction & Linking located in Cologne is looking for a Research Associate Knowledge Graphs (Salary group 13 TV‑L, working time up to 100 %, limited to 31 December 2027).

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.

The EU‑funded project GRAPHIA aims to advance the use of computational methods and Open Science practices to enhance the analytical potential of research in the social sciences and humanities (SSH), particularly in the areas of social inequality, demographic change, migration, armed conflict, misinformation, and cultural heritage. By developing a comprehensive knowledge graph for SSH and integrating applications based on artificial intelligence and large language models, GRAPHIA will convert heterogeneous SSH data into more interoperable and machine‑readable formats. This infrastructure is expected to strengthen capacities for data visualisation and analysis, facilitate the identification of patterns in unstructured data, and support more systematic investigation of social and cultural dynamics.

Our Benefits:

• A fast growing and international working environment with access to unique datasets
• Excellent career opportunities in software development and data engineering
• 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

Contact

For further information concerning the tasks please contact Dr. Benjamin Zapilko viaphone [phone] or via E‑Mail ([e-mail]). If you have questions about the application process, please contact Franca Tosetti via E‑Mail ([e-mail]).

Your profile:

• Scientific University degree (Master) in Computer Science or related fields
• Research interests in one or more of the following topics: knowledge graphs, information extraction, machine learning or artificial intelligence
• Expertise in software development with Python, database and search engine technologies, machine learning frameworks, semantic web technologies, Docker
• Desired: expertise in working with scholarly data, metadata‑ and web standards
• Ability to communicate fluently in English, basic knowledge of the German language desirable

Your tasks will be:

• Implementation of approaches for lifting (meta‑)data into RDF and for integrating it into the GRAPHIA knowledge graph
• Adoption and evaluation of information extraction pipelines to identify mentions of entities in scholarly resources
• Collaborating in respective work packages in the GRAPHIA project with other project partners
• Applied research in fields like knowledge graphs, information extraction, machine learning or artificial intelligence in the context of scholarly data
• Publication of research and project results

Please apply via our Online‑application portal until 12 February 2026. Our reference number is KTS‑75.