Technische Universität München
Other Position

Student Assistants for 8-15 hours/week: AI for Clinical Decision Support (VIOLET Project) | Institute for AI and Informatics in Medicine | TUM

Deadline
Mar 04, 2027
Closing in 136 days
Location
N/A
Germany
Employment
None
Part time
Reference
N/A
Posted Sep 08, 2026

About the role

Chair of Medical Informatics Institute for AI and Informatics in Medicine TUM Student Assistants for 8-15 hours/week: AI for Clinical Decision Support (VIOLET Project) Institute for AI and Informatics in Medicine TUM

04.09.2026, Student assistants, internships, student research projects

Student Assistants for 8-15 hours/week at the Chair of Medical Informatics, Institute for AI and Informatics in Medicine

Passing a medical licensing exam is one thing. Supporting a real clinical decision with incomplete data, rare edge cases, and a physician waiting for an answer is another problem entirely.

Our research group AI for Women's Health is hiring student assistants to work on the VIOLET project , a nationally funded initiative developing a hybrid AI framework for guideline-based treatment decision support in gynecological oncology. The work combines knowledge graphs, retrieval- augmented generation (RAG), and LLM-based multi-agent systems and is grounded in real clinical data from the TUM University Hospital's data integration center.

Your job will be to help make these systems work reliably in practice: probing where foundation models fail to follow clinical reasoning, building evaluation pipelines that go beyond standard benchmarks, and developing methods to extract structured knowledge from clinical text.

What we're looking for:
  • Bachelor's or Master's student in Computer Science, Mathematics, Physics, or a related field
  • Solid Python and PyTorch skills
  • Genuine curiosity about the gap between model performance and clinical reliability
  • Rigor in how you think, code, and document
  • Prior experience in medical AI is welcome but not the deciding factor
  • What you get:
  • Access to real, curated clinical datasets within a regulated research environment
  • Substantial GPU infrastructure
  • A short feedback loop between technical work and clinical application
  • Both engineering and clinical mentorship within the team
  • If this sounds like the kind of problem you want to dig into every day, send a cover letter, CV and transcripts to [email protected].

    Feel free to also share a GitHub link if you'd like to share your programming experience.

    Kontakt: [email protected]

    How to apply

    Read the full posting, then apply through the employer's own site. Applications are handled by the institution, not by AcademicGates.