Researcher / Postdoctoral Researcher (m/f/d) Computer Science / Data Science

The Biomedical Informatics and Genetic Phenotype Redefinition Research Group at the Institute of Clinical Molecular Biology (IKMB), Kiel University (CAU), and the University Medical Center Schleswig-Holstein (UKSH), invites applications for a full-time researcher or postdoctoral researcher position in computer science, data science, biomedical informatics, or a related field.

 

The position is embedded in the Cluster of Excellence “Precision Medicine in Chronic Inflammation” (PMI) and contributes to RTF-VIII Area 1b - LLM Data Browser & Query Layer. The aim of this project is to develop a lightweight, secure, and auditable query layer that enables structured access to metadata, data availability, and approved aggregate summaries across biomedical and clinical data environments. The system is intended to support exploratory readiness assessment and structured navigation of metadata and data availability and is not designed to perform predefined clinical analyses.

 

A central aspect of the work will be the design and implementation of software components for an LLM-supported data browser, including structured tool interfaces, secure query handling, and auditable, governance-aware software architecture. The project is situated at the interface of software engineering, biomedical data science, metadata integration, and AI-supported research infrastructure.

 

Our group develops computational and statistical methods for large-scale genomic, clinical, and phenotypic data and collaborates closely with partners in computer science, genomics, and inflammation medicine. Within PMI, the successful candidate will work in an interdisciplinary and highly collaborative environment with strong links to biomedical data science and precision medicine.

 

Join our team

Join our team and support us as soon as possible, initially on a fixed-term contract for 3 years, with the possibility of extension subject to performance and funding availability.

 

What we offer you:

• A full-time position according to TV-L E13 (100%), subject to collective bargaining regulations
• An interdisciplinary research environment at the interface of computer science, AI, and precision medicine
• Access to excellent collaborations within Kiel University, UKSH, and the PMI Excellence Cluster
• Opportunities for scientific exchange, conferences, and further training
• Flexible working conditions and support for balancing family and professional life

 

What you can expect:

• Design and implement secure software components for metadata and query layers in biomedical data environments
• Develop and maintain structured, auditable, and permission-aware interfaces for an LLM-supported data browser
• Work on APIs, metadata schemas, structured outputs, logging, and containerized services
• Contribute to reproducible research software, including testing, documentation, and deployment
• Collaborate with interdisciplinary partners and optionally contribute to teaching and supervision 

 

Your profile:

• PhD or strong Master’s degree in computer science, data science, software engineering, biomedical informatics, or a related quantitative field; outstanding candidates at either level are encouraged to apply
• Strong programming skills, especially in Python; experience with TypeScript/JavaScript, Go, Rust, Java, or R is a plus
• Solid experience with Linux-based development, Git, testing, debugging, and modern software engineering practices
• Familiarity with APIs, structured data formats, containerization, reproducible environments, and ideally AI/LLM-supported development workflows (e.g., tool-based LLMs, retrieval systems, AI coding assistants)
• Very good English skills, strong motivation for interdisciplinary collaboration, and ideally experience in biomedical or data-rich research contexts (not required) 

 

We look forward to receiving your application (cover letter, CV, academic transcripts and degree certificates, and the names and contact details of two references) by 03.05.2026, quoting reference number 28396.