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Postdoc in NLP and Research Knowledge Graphs (KTS-80)
Gesis · Köln · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Gesis |
| Title | Postdoc in NLP and Research Knowledge Graphs (KTS-80) |
| Normalized title | - |
| Department / team | Knowledge Technologies for the Social Sciences / Köln - Online & persönl. Interview |
| Location | Köln |
| Work model | - |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2026-05-28 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Gesis. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Personio. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in Knowledge Technologies for the Social Sciences. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Gesis |
| Source | 1bd103b0-7729-4766-8460-209457de0790 |
| ATS provider | Personio |
Description
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 1. October 2026 our Department Knowledge Technologies for the Social Sciences (KTS) , Team Information and Data Retrieval located in Cologne is looking for a
Postdoc in NLP and Research Knowledge Graphs
(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:
Master's degree and completed a PhD in computer science, data science, or a related field Experience in project management 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
Our Benefits:
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 Philipp Mayr via phone +49 221 47694 533 o r via E- Mail ([email protected]). If you have questions about the application process, please contact Christine Laßmann via E-Mail ([email protected]).
Interested?
Please apply via our Online-application portal until June 17th, 2026.
Our reference number is: KTS-80
Full job record
| Job ID | a7be50822feb92df1d8deba229c2b75a624bd5bd |
| Org ID | 2f49d8f4-ba59-4851-a149-34e64c8ee4e5 |
| Source ID | 1bd103b0-7729-4766-8460-209457de0790 |
| Board ID | 1bd103b0-7729-4766-8460-209457de0790 |
| Provider | personio |
| Provider Job Key | 2649886 |
| Title | Postdoc in NLP and Research Knowledge Graphs (KTS-80) |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Köln |
| Department | Knowledge Technologies for the Social Sciences |
| Team | Köln - Online & persönl. Interview |
| Employment Type | full_time |
| Workplace Type | — |
| Remote Policy | — |
| Country | Köln |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://gesis.jobs.personio.de/job/2649886?language=en |
| Apply URL | https://gesis.jobs.personio.de/job/2649886?language=en |
| First Seen At | 2026-05-30 05:42:40Z |
| Last Seen At | 2026-06-06 07:50:47Z |
| Last Checked At | 2026-06-06 07:50:47Z |
| Last Changed At | 2026-05-30 05:42:40Z |
| Inactive At | — |
| Source Posted At | 2026-05-28 10:18:14Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=personio/board=gesis.de/date=2026-06-06/2026-06-06T07-50-46-858Z-82deaab8cd881b259b974d83730fc6736dd7fc95e9b48c45f0e3e8bfe544d6cd.json |
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