
Aktiviere Job-Benachrichtigungen per E-Mail!
Erstelle in nur wenigen Minuten einen maßgeschneiderten Lebenslauf
Überzeuge Recruiter und verdiene mehr Geld. Mehr erfahren
A leading university hospital in Germany seeks a highly qualified Postdoc to develop AI models for tumor segmentation and dose accumulation in radiotherapy. Candidates should have a PhD in Medical Physics, Biomedical Engineering, or Computer Science and excellent skills in Python and deep learning. This is a 36-month position with a competitive salary under public sector agreements, located at the LMU Klinikum Großhadern, offering a collaborative and stimulating research environment.
Workplace: Campus Großhadern
Working hours: Full time
Institution: Klinik und Poliklinik für Strahlentherapie und Radioonkologie
Department: Research Group
Date of entry: 01.02.2026
Application deadline: 15.01.2026
Reference Number: 2025-K-0446
The Hospital of the University of Munich, Germany, is one of the largest and most competitive university hospitals in Germany and Europe. 48 specialized hospitals, departments and institutions harbouring excellent research and education provide patient care at the highest medical level with around 11.000 employees.
In a multi-institutional research project funded by the German Federal Ministry of Research, Technology and Space, a Postdoc position investigating the use of uncertainty-aware AI models for auto-segmentation and dose accumulation in radiotherapy treatment planning is open at the Department of Radiation Oncology of the LMU Munich University Hospital (PD Christopher Kurz & Prof. Guillaume Landry) from February 2026. The candidate will collaborate with our project partners at the Fraunhofer Institute for Industrial Mathematics (ITWM) Kaiserslautern (Prof. Karl-Heinz Küfer) and the LMU Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence (Prof. Gitta Kutyniok). The project will employ state-of-the‑art AI models for auto-segmentation and deformable image registration in the scope of MRI‑guided adaptive radiotherapy. Focus will be set on uncertainty estimation by these models and their integration into robust radiotherapy treatment planning.
089 4400 76762
Please use the Online-Form for your application. Disabled persons will be preferentially considered in case of equal qualification. Presentation costs cannot be refunded.
Please note that we cannot reimburse travel expenses incurred through interviews.
We ask you for your understanding that postal applications will not be returned, but will be destroyed in accordance with data protection regulations. The data usage information also applies to postal applications.