Postdoctoral Researcher -- Biomedical Semantics, Ontologies, and Large Language Model Integration
Drucken
Heidelberg
Informationen zur Anzeige:
Postdoctoral Researcher -- Biomedical Semantics, Ontologies, and Large Language Model Integration
Heidelberg
Aktualität: 13.08.2026
Anzeigeninhalt:
13.08.2026, Deutsches Krebsforschungszentrum (DKFZ)
Heidelberg
Postdoctoral Researcher -- Biomedical Semantics, Ontologies, and Large Language Model Integration
Aufgaben:
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.
Qualifikationen:
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
Berufsfeld
Öffentlicher Dienst, Verwaltung
Forschung, Lehre
Forschung & Entwicklung
Informationstechnologie, TK
IT/TK Softwareentwicklung
Softwareentwicklung
Bundesland
Standorte
