Postdoctoral researcher in the AI in Radiation Oncology group, TUM Klinikum rechts der Isar

20.02.2026, Wissenschaftliches Personal

Join an ERC-funded research project at the Department of Radiation Oncology, TUM Klinikum Rechts der Isar, focused on developing next-generation AI systems for radiotherapy target volume definition. Our research aims to advance beyond classical segmentation networks toward multimodal, prompt-based, and foundation-model approaches for clinically deployable medical AI. Your responsibilities: • Develop and evaluate novel multimodal vision-language models for prompt-based 3D medical image segmentation • Work with large-scale clinical CT datasets and scalable deep learning pipelines • Validate models in close collaboration with radiation oncologists and medical physicists • Publish research findings at leading international venues • Support junior researchers and contribute to international collaborations Requirements: • PhD in machine learning, medical image computing, biomedical engineering, medical physics or related field • Strong Python and PyTorch experience • Solid publication record and ability to communicate research results effectively • Experience in medical imaging and/or radiotherapy research • Strong interest in translational AI with potential impact on patient care Highly desirable: • Experience with 3D medical image segmentation, foundation models, or vision-language models • Familiarity with radiotherapy workflows • Clinical scripting experience (e.g., Varian Eclipse / ARIA) What we offer: • ERC-funded full-time postdoctoral position (TV-L E13) up to 5 years • International collaboration to build a large radiotherapy dataset • Dedicated GPU infrastructure • Strong collaborations within TUM’s AI ecosystem • High-impact publication potential • Employee benefits: EGYM Wellpass, corporate discounts (e.g., Käfer), and bike leasing (JobBike Bavaria) • Workplace in central Munich (Max-Weber-Platz) with excellent public transport access Contact: Josef Buchner, MD, Department of Radiation Oncology, TUM Klinikum rechts der Isar, Technical University of Munich (TUM), Ismaninger Str. 22, 81675 Munich Email: j.buchner@tum.de Applications will be considered until the positions are filled. In cases of equal suitability, candidates with disabilities will be given preference. We regret that we are unable to reimburse any travel expenses associated with the interview process. We look forward to your application!

Join an ERC-funded research project at the Department of Radiation Oncology, TUM Klinikum Rechts der Isar, focused on developing next-generation AI systems for radiotherapy target volume definition.

Our research aims to advance beyond classical segmentation networks toward multimodal, prompt-based, and foundation-model approaches for clinically deployable medical AI.

Your Responsibilities

• Develop and evaluate novel multimodal vision-language models for prompt-based 3D medical image segmentation
• Work with large-scale clinical CT datasets and scalable deep learning pipelines
• Validate models in close collaboration with radiation oncologists and medical physicists
• Publish research findings at leading international venues
• Support junior researchers and contribute to international collaborations

Requirements

• PhD in machine learning, medical image computing, biomedical engineering, medical physics, or related field
• Strong Python and PyTorch experience
• Solid publication record and ability to communicate research results effectively
• Experience in medical imaging and/or radiotherapy research
• Strong interest in translational AI with potential impact on patient care

Highly Desirable

• Experience with 3D medical image segmentation, foundation models, or vision-language models
• Familiarity with radiotherapy workflows
• Clinical scripting experience (e.g., Varian Eclipse / ARIA)

What We Offer

• ERC-funded full-time postdoctoral position (TV-L E13) up to 5 years
• International collaboration to build a large radiotherapy dataset
• Dedicated GPU infrastructure
• Strong collaborations within TUM’s AI ecosystem
• High-impact publication potential
• Employee benefits: EGYM Wellpass, corporate discounts (e.g., Käfer), and bike leasing (JobBike Bavaria)
• Workplace in central Munich (Max-Weber-Platz) with excellent public transport access

Technical University of Munich (TUM)
Ismaninger Str. 22

Email: j.buchner@tum.de

Applications will be considered until the position is filled. In cases of equal suitability, candidates with disabilities will be given preference.

We regret that we are unable to reimburse any travel expenses associated with the interview process.

We look forward to your application!

Kontakt: j.buchner@tum.de