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Postdoc in Evaluation & Benchmarking of AI Models
Gesis · Köln · Deleted · Personio
Job facts
| Field | Value |
|---|---|
| Company | Gesis |
| Title | Postdoc in Evaluation & Benchmarking of AI Models |
| Normalized title | - |
| Department / team | Knowledge Technologies for the Social Sciences / Köln - Online & persönl. Interview |
| Location | Köln |
| Work model | - |
| Employment type | Full Time |
| Salary | - |
| Status | deleted |
| ATS provider | Personio |
| Posted / first seen | 2026-05-27 / 2026-05-30 |
| Changed / last seen | 2026-06-06 / 2026-06-03 |
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 01.10.2026 our Department Knowledge Technologies for the Social Sciences (KTS) , Team Information Extraction & Linking located in Cologne is looking for a
Postdoc in Evaluation & Benchmarking of AI Models
(Salary group 13 TV-L, working time 100%, limited till 31.12.2028, subject to approval)
The department Knowledge Technologies for Social Sciences 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 and BERD@NFDI projects, 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 and BERD projects including coordination with project partners and supervision of PhD students Conduct research in the context of AI benchmarking and scholarly information extraction Advance the GESIS Methods Hub through community engagement, content acquisition (methods, tutorials, training material) and integration with third party infrastructures (NFDI4DS, BERD@NFDI) and the incorporation of benchmarking protocols and datasets Exchange with the relevant scientific communities and dissemination of project results through publications and workshops
Your profile:
Completed a PhD in computer science, data science, or a related field Proven experience in scholarly information extraction, benchmarking and evaluation frameworks for AI systems Very good experience in software development with Python, AI-tooling, NLP technologies and Database database technologies Very good verbal and written communication skills in German; very good knowledge of English
Our Benefits:
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 Dimitar Dimitrov via phone +49 221 47694512 or via E-Mail ([email protected]). If you have questions about the application process, please contact Franca Tosetti via E- Mail ([email protected]).
Interested?
Please apply via our Online-application portal until 03.06.
Our reference number is: KTS-79-intern
Full job record
| Job ID | adc05be5da9711f208f5b688a052446fadfcd23e |
| 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 | 2648962 |
| Title | Postdoc in Evaluation & Benchmarking of AI Models |
| Normalized Title | — |
| Status | deleted |
| Active | no |
| 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/2648962?language=en |
| Apply URL | https://gesis.jobs.personio.de/job/2648962?language=en |
| First Seen At | 2026-05-30 05:42:40Z |
| Last Seen At | 2026-06-03 12:35:10Z |
| Last Checked At | 2026-06-06 07:50:47Z |
| Last Changed At | 2026-06-06 07:50:47Z |
| Inactive At | 2026-06-06 07:50:47Z |
| Source Posted At | 2026-05-27 11:46:23Z |
| Source Updated At | — |
| Raw Payload Uri | s3://bluework-jobs-prod-raw-590183727216/raw/provider=personio/board=gesis.de/date=2026-06-03/2026-06-03T12-35-09-670Z-617c02394e50728566a96afb525eb73f95c3c32c2facdd0bbdfdcf9f82a9605f.json |
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"value": "<span style=\"font-family:Tahoma, Geneva, sans-serif;font-size:15px;\">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.<br> <br>Starting on <strong>01.10.2026 </strong>our Department <strong>Knowledge Technologies for the Social Sciences (KTS)</strong>, <strong>Team Information Extraction & Linking</strong> located in <strong>Cologne</strong> is looking for a<br> <br><strong>Postdoc in Evaluation & Benchmarking of AI Models</strong><br><strong>(Salary group 13 TV-L, working time 100%, limited till 31.12.2028, subject to approval)</strong><br> <br>The department <a href=\"https://www.gesis.org/en/institute/departments/knowledge-technologies-for-the-social-sciences\"><strong><span style=\"line-height:115%;\">Knowledge Technologies for Social Sciences</span></strong></a></span><span style=\"font-family:Tahoma, Geneva, sans-serif;font-size:15px;\"> 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. <br>AI is transforming the scientific process across disciplines. In the NFDI4DS and BERD@NFDI projects, 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. </span>"
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"value": "<ul style=\"list-style-type:disc;margin-left:15.05px;\"><li style=\"font-family:Tahoma, Geneva, sans-serif;font-size:15px;\">Lead dedicated work packages and a team of researchers within the NFDI4DS and BERD projects including coordination with project partners and supervision of PhD students</li><li style=\"font-family:Tahoma, Geneva, sans-serif;font-size:15px;\">Conduct research in the context of AI benchmarking and scholarly information extraction</li><li style=\"font-family:Tahoma, Geneva, sans-serif;font-size:15px;\">Advance the GESIS Methods Hub through community engagement, content acquisition (methods, tutorials, training material) and integration with third party infrastructures (NFDI4DS, BERD@NFDI) and the incorporation of benchmarking protocols and datasets</li><li style=\"font-family:Tahoma, Geneva, sans-serif;font-size:15px;\">Exchange with the relevant scientific communities and dissemination of project results through publications and workshops</li></ul>"
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