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Ludwig Maximilian University of Munich

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PhD in Clinical AI and Medical Data Science at LMU Munich Ludwig Maximilian University of Munich in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

Salary according to TV-L E13; full-time or part-time possible.

Deadline

Oct 2, 2026

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Country

Germany

University

Ludwig Maximilian University of Munich

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Keywords

Computer Science
Deep Learning
Biology
Predictive Modeling
Nlp
Medical Science
Survival Analysis
Clinical Data
Statistics
ML

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About this position

PhD opening at Ludwig Maximilian University of Munich, Medical Faculty / Pathologisches Institut, with Dr. Philipp Keyl. The project is in Clinical AI and Medical Data Science, focusing on processing and harmonizing heterogeneous clinical and longitudinal datasets and developing ML-based methods for clinical outcomes.

Research topics include machine learning, deep learning, transformer architectures, LLMs, NLP, survival analysis, and predictive modeling in a personalized oncology setting. This is a strong fit for applicants with a background in Computer Science, Medical Informatics, Bioinformatics, Statistics, AI, or related fields.

Required skills include strong Python and PyTorch experience, plus prior work with time-series data, clinical/biomedical data analysis, or survival modeling. The position is based in Munich, Germany.

Funding is provided as TV-L E13, with the option of full-time or part-time employment. The deadline is 2026-10-02.

To apply, send a single PDF (max 10 MB) to [email protected] and include the job posting number DM-09/1-2026. The official posting is available via the LMU job portal.

Funding details

Salary according to TV-L E13; full-time or part-time possible.

What's required

Master's degree in Data Science, Computer Science, Medical Informatics, Bioinformatics, Statistics, AI, or a related field. Strong Python and PyTorch skills are required, along with experience in machine learning/deep learning, time-series data, NLP/LLMs, transformer architectures, clinical/biomedical data analysis, or survival analysis.

How to apply

Send a single PDF application (max 10 MB) by email to [email protected] and cite job posting number DM-09/1-2026. Use the LMU job portal link for the official posting.

More information can be found here

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