Postdoctoral Position in Language Models for Pediatric Data Analysis at ETH Zurich (Medical AI, Computer Science) ETH Zurich in Switzerland

ETH Zurich is inviting applications for a postdoctoral research position focused on "Language Models for Pediatric Data Analysis" in collaboration with the University Children's Hospital Basel. The successful candidate will join the Medical AI Lab at ETH Zurich (D-BSSE, Basel) and work closely with clinicians, clinical coders, and IT infrastructure teams to develop, validate, and safely deploy large language models (LLMs) for automated coding of pediatric diagnoses from electronic health records (EHRs). The project aims to enhance research capabilities and clinical data usability through advanced machine learning and artificial intelligence techniques.

The position is embedded in a vibrant interdisciplinary environment, with access to the ETH AI Center and SwissAI initiative, providing opportunities for collaboration and professional growth. The role involves model development, rigorous validation on new benchmarks, and safe deployment of locally hosted LLMs. Additional responsibilities include publishing research results in top-tier venues and contributing to the group’s engagement with the broader AI and medical informatics communities.

Applicants should have a PhD in Computer Science, Medical AI, Medical Informatics, or a closely related field. Required skills include strong programming abilities in Python, experience with modern ML/AI/LLM stacks (such as PyTorch, HuggingFace, Ollama, vllm), and proficiency in German at C1 level or higher for analyzing local patient records. Experience with clinical NLP, retrieval-augmented generation (RAG), vector databases, Docker, GPU-based infrastructure, and medical data coding (ICD-10) is highly desirable. Candidates should demonstrate good computational engineering practices and the ability to work both independently and collaboratively in a diverse team. Effective communication in English and German is essential.

The position is fully funded and offers access to state-of-the-art computational resources, including large GPU clusters, and direct clinical collaborations. ETH Zurich is committed to diversity, equality of opportunity, and sustainability, fostering an inclusive and supportive environment for all staff and students.

To apply, candidates must submit their application online via the ETH Zurich application portal, including a CV, Bachelor and Master transcripts, a motivation letter, and letters of recommendation (or a list of referees). Applications sent via email or postal services will not be considered. For further information about the research group, visit the provided academic page. Questions regarding the position can be directed to Prof. Michael Moor’s lab email (no applications via email).

Keywords: Language Models, Pediatric Data Analysis, Medical AI, Clinical NLP, Electronic Health Records, Machine Learning, Artificial Intelligence, Biomedical Informatics.