The German Cancer Research Center (DKFZ) is one of Europe’s largest cancer research centers. “Research for a life without cancer" is the mission of our world-class scientists and all our team members.
The DKFZ is a place where the brightest minds pursue bold ideas and seek answers to pioneering scientific questions through collaboration, innovation, and exploration across many disciplines. We provide a dynamic environment which empowers excellence with state-of-the-art technologies, cutting edge infrastructure, and a global scientific network.
Contribute your knowledge, vision, and dedication to create a space where scientific discovery in cancer research is transformed into benefits for human health.
The Department of Radiooncology / Radiobiology is seeking, starting from September 15, a
Postdoctoral Researcher — Biomedical Semantics, Ontologies, and Large Language Model Integration
Reference number: 2026-0157
- Heidelberg
- Full-time
- Radiooncology / Radiobiology
Your Tasks
We are seeking a highly motivated postdoctoral researcher to join an interdisciplinary project at the intersection of biomedical informatics, semantic technologies, and large language models (LLMs). The position is embedded in the MIRO-LLMs initiative (Helmholtz Metadata Collaboration), which focuses on advancing machine-interpretable research objects through ontology-driven approaches and AI-assisted knowledge integration.
The successful candidate will contribute to the design and implementation of domain ontologies, knowledge graphs, and semantic data models that enable structured integration of biomedical research data with LLM-based systems. The role involves close collaboration with data scientists, clinicians, and AI researchers to ensure semantic interoperability, FAIR data principles, and robust metadata standards across heterogeneous datasets.
Key responsibilities include developing and maintaining ontologies using OWL/RDF, implementing semantic pipelines and APIs, integrating structured knowledge with LLM workflows, and contributing to research publications and open-source tools development.
Equivalent training will be provided to be up to date with our methodology.
Your Profile
- Master's degree in life sciences, computer science, mathematics, physics, or engineering with strong computational and data analysis skills
- A good knowledge of programming in Python, R, or similar
- Experienced with semantic web technologies such as SPARQL and RDF triple stores
- Experienced with graph databases and knowledge graphs for biomedical data integration
- A solid understanding of biomedical data contexts such as in preclinical and clinical trials, imaging, or omics
- Familiarity with data standards such as CDISC, FHIR, OMOP Common Data Model (CDM), and OBO ontologies is highly desirable
- Team player with good English proficiency
