Job description
As part of your role, you will design and implement LLM-based agent systems that structure and process materials science data. In doing so, you will develop data and agent architectures for integrating heterogeneous sources and enabling knowledge extraction. You will create semantic representations such as ontologies, knowledge graphs, or RDF/SPARQL models, connect large language models to databases, simulation data, and formal models, and implement the necessary logic for data access, provenance, reproducibility, and traceability. Your responsibilities will also include the scientific documentation, evaluation, and publication of your research results in international peer-reviewed journals and conferences.
Starting date
01.04.2026
Personal qualification
You have:
1. A completed academic university degree (Diplom (University) / Master’s degree) in computer science, physics, materials science, data science, or a related field, ideally with a completed doctorate
2. Very good knowledge of software development (in particular Python and JavaScript/TypeScript)
3. Experience with LLMs beyond prompt engineering, e.g., tool use, agent control, state management, retrieval, and workflow integration
4. Solid knowledge of data models, APIs, and structured data processing
5. Ability to work independently in scientific research and collaborate in interdisciplinary environments