Postdoc in NLP and Research Knowledge Graphs (KTS-86)

GESIS - Leibniz Institut für Sozialwissenschaften; Deutschland; On-site; EUR 65,000 - 75,000; Full time

Benefits offered by this job

Childcare subsidies

Health management program

Pension plan

Training opportunities

Job summary

GESIS – Leibniz-Institute for the Social Sciences in Germany seeks a Postdoctoral Researcher to lead research on scholarly information extraction, develop Knowledge Graphs, and advance AI-driven data services. The role coordinates with the Knowledge Technologies for the Social Sciences (KTS) team in Cologne, collaborating with international partners.

Starting Dec 1, 2026, the position is 100% with long-term scope.

Qualifications

• Completed academic university degree (Master’s or equivalent) and completed PhD in computer science, data science, or a related field.
• Experience in project management and supervising PhD students
• Proven experience in NLP research and knowledge graphs, specifically in the context of scholarly information extraction.
• Very good experience in software development with Python, AI-tooling, NLP technologies and database technologies
• Very good verbal and written communication skills in English; good knowledge of German desirable

Responsibilities

• Lead dedicated work packages and a team of researchers within the NFDI4DS project including coordination with project partners and supervision of PhD students
• Research scholarly information extraction and develop methods for building Research Knowledge Graphs (e.g., GESIS KG )
• Develop, integrate, and evaluate services, models, and systems using established benchmarks
• Advance the NFDI4DS Academy through community engagement, content acquisition (methods, tutorials, training material) and integration with third party infrastructures
• Exchange with scientific and user communities and dissemination of project results through publications and workshops at national and international level

Skills

NLP research

Knowledge graphs

Python

AI tooling

Supervision of PhD students

English communication

German language (desirable)

Project management

Education

Master’s degree

PhD in computer science / data science / related field

Job description

Organisation/Company GESIS - Leibniz Institut für Sozialwissenschaften Department Cologne/Mannheim Research Field Sociology » Other Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 2 Nov 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number KTS-86 Is the Job related to staff position within a Research Infrastructure? No

Offer 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 on December 1, 2026 our Department Knowledge Technologies for the Social Sciences (KTS), Team Information and Data Retrieval located in Cologne is looking for a Postdoctoral Researcher (Salary group 13 TV-L, working time 100%, limited till 31.12.2028, subject to approval).

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.

AI is transforming the scientific process across disciplines. In the NFDI4DS project, we develop infrastructures that empower researchers to responsibly adopt AI methods—for example, by establishing fair benchmarking protocols, ensuring transparent evaluation and documentation of AI models and LLMs, and curating a repository of open, reusable AI-based methods, along with related training materials and events. In this context, we are seeking a motivated researcher to coordinate and lead these activities.

Your tasks will be:

• Lead dedicated work packages and a team of researchers within the NFDI4DS project including coordination with project partners and supervision of PhD students
• Research scholarly information extraction and develop methods for building Research Knowledge Graphs (e.g., GESIS KG )
• Develop, integrate, and evaluate services, models, and systems using established benchmarks
• Advance the NFDI4DS Academy through community engagement, content acquisition (methods, tutorials, training material) and integration with third party infrastructures
• Exchange with scientific and user communities and dissemination of project results through publications and workshops at national and international level

Your profile:

• Completed academic university degree (Master’s or equivalent) and completed PhD in computer science, data science, or a related field
• Experience in project management (Strong mentoring and communication skills to effectively supervise and support PhD students)
• Proven experience in NLP research and knowledge graphs, specifically in the context of scholarly information extraction.
• Very good experience in software development with Python, AI-tooling, NLP technologies and database technologies
• Very good verbal and written communication skills in English; good knowledge of German desirable
• A growing, international work 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. Philipp Mayr via phone [phone] or via E-Mail ( [e-mail] ).

Interested?