Research Data Manager (PostDoc) for mapping harvesting relationships (KTS-84)
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Position Overview & Specifications
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 October 1, 2026 our Department Knowledge Technologies for the Social Sciences (KTS), Team FAIR Data located in Cologne, is looking for a
Research Data Manager (PostDoc) for mapping harvesting relationships
(Salary group 13 TV-L, working time 100 %, limited for three years)
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.
The HaFER project’s goal is to improve the visibility of German research data by identifying how metadata is propagated between the many services collecting such data. For this, we will build a map that will identify which data services harvest which metadata, and how metadata are transformed in the process. Based on this map we will offer best practices to the data services, negotiate with harvesters on how to present metadata better. The positions requires both networking capabilities within the relevant communities as well as technical skills to wrangle, model and analyze the metadata.
Your tasks will be:
- Managing and coordinating the HaFER project to make it a success
- Setting-up automated systems for metadata collection with the help of AI tools
- Networking within the NFDI and other research data organizations to help promote the goals of HaFER, including organization of networking events
- Conducting research in the topics of the department
Your profile:
- Completed academic university degree (Master’s or equivalent) and completed PhD in Computer Science, Social Science or related subjects
- Experience in Research Data Management, for example in the context of the National Research Data Infrastructure (NFDI), or with services that harvest research metadata
- Experience in handling, curating, harvesting and/or extracting research metadata on a technical level
- Proven research record in the topics of the department, preferably Knowledge Graphs and/or Information Extraction
- Excellent English skills are a must, German language skills are a plus
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 contact person via E-Mail (
Candidate Selection & Onboarding Process
Application & Resume Screening
Submit your tailored CV/Resume directly to the talent acquisition portal.
Technical & Competency Interviews
Virtual interviews with the hiring manager and multidisciplinary team.
Formal Offer & Benefits Negotiation
Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.
Onboarding & Corporate Integration
Equipment provisioning, team orientation, and commencement of duties.
United States Work Authorization & Sponsorship Guide
Under United States immigration law (INA § 101(a)(15)(H)), foreign nationals seeking full-time professional positions typically navigate either non-immigrant specialty occupation classifications or immigrant visa sponsorship:
Requires a relevant Bachelor's degree or higher. Employers must file an approved Labor Condition Application (LCA) with the US Department of Labor confirming the prevailing wage rate.
Canadian and Mexican citizens qualify under USMCA (TN status). F-1 STEM graduates benefit from 36-month aggregate work authorization through E-Verify enrolled employers.
Candidate Preparation Blueprint: Technology
Based on transatlantic hiring benchmarks for Research Data Manager (PostDoc) for mapping harvesting relationships (KTS-84) roles across GESIS – Leibniz-Institut für Sozialwissenschaften's corporate sector, successful applicants typically excel across three core dimensions:
Demonstrated portfolio evidence, architecture/system design case studies, or validated professional certifications directly applicable to Technology.
STAR method competency responses highlighting cross-functional leadership, conflict resolution, and delivering measurable enterprise ROI under tight timelines.
Total compensation expectation aligned within the benchmarked Salary Disclosed on Application bracket, including retirement vesting and health parity.
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