Awesome research project in clinical LLM
Studentische Hilfskraft (m/w/d) – LLM-Semantik & klinische Ontologien (Radiologie/Onkologie) – bis 20 Std./Woche. Duration: 6 months
28.10., Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten
Student assistant (up to 20 h/week): test LLM semantics with clinical ontologies in radiology/oncology—ontology mapping, data curation, annotation QA, simple Python, and evaluating embeddings. Python required; NLP is a plus. Please send your .txt CV to .
Student assistant (m/f/d) for BMBF project at TUM: Testing LLM semantics with clinical ontologies (radiology/oncology). Tasks: Ontology mapping, data preparation, annotation QA, small Python scripts and evaluation of embeddings. Must-haves: Enrolment, Python, CSV/JSON, German C2. Working mode: Presence in Munich (Einsteinstraße), no purely remote work. Scope: up to 20 hours/week.
We are looking for a student assistant to support a project reviewing the semantics of large language models (LLMs) using
clinical ontologies in radiology/oncology. Tasks include data preparation, annotation/quality assurance and simple experiments
(embeddings vs. reference ontologies).
Duration: 6 Months
Your tasks
- Support with ontology mapping & data maintenance (radiological/oncological texts)
- Preparation & quality assurance of annotations; simple scripts for data cleansing
- Research & documentation of results in German/English
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Your profile
Must-haves (required):
- Enrolment in computer science, medical informatics, data science or similar (student assistant) - Basic knowledge of Python and
working with CSV/JSON - German C2 (for documentation/coordination), good English skills - Careful, structured way of working; availability
up to 20 hours/week
- Willingness to be present regularly at the Munich (Einsteinstraße)
Plus (not required):
- Experience with medical terminology/ontologies or NLP
- Experience with annotation/QA and clean code habits
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We offer
- Flexible working hours (on-site), central location (Einsteinstraße)
- Insight into clinical AI research and teamwork
Access to GPUs and modern tools
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Application
Please send your CV, preferably as a .txt file, to and, preferably, write the email yourself.
The position is suitable for severely disabled persons. Severely disabled applicants will be given preference if they are otherwise
essentially equally qualified, capable and professionally competent.
Data protection: Please note the data protection information for applicants at TUM
Equality: We promote equal opportunities and diversity.
Fixed-term contract: Employment as a student assistant (SHK) in accordance with the applicable TUM guidelines.