TUM Postdoc in Computer Science Institute for AI and Informatics in Medicine 2026

Are you passionate about making Artificial Intelligence (AI) in medicine transparent, trustworthy, and clinically relevant? Join the VIOLET Project: a pioneering research initiative to develop an explainable and interoperable methodological framework for AI in gynecological oncology.

As a senior member of our research team, you will take intellectual and operational leadership for key technical and methodological work packages:

• Drive technical outcomes and provide quality assurance for research and software development tasks
• Define the overall architecture of the VIOLET research prototype, focusing on its role as a methodological demonstrator and ensuring interoperability with Medical Informatics Initiative (MII)/FHIR standards
• Design and implement methodological concepts and software for benchmarking frameworks for AI evaluation
• Independently develop and implement research ideas within the VIOLET research framework
• Work closely with doctors and data scientists to ensure the developed systems meet clinical needs and are validated against real-world scenarios
• Mentor and supervise PhD candidates and student assistants
• Contribute to project governance and represent the project in steering committee meetings

Table of Content

• Summary
• Benefits
• Requirements
• Application Deadline
• How To Apply

Summary

• Application DeadlineNot Specified
• Study LevelPostdoctoral Fellowships
• SponsorTechnical University of Munich (TUM)
• School to studyTechnical University of Munich (TUM)
• Eligible CountryAll Countries

Benefits

• The opportunity to work on cutting-edge research projects with high societal impact
• A senior, independent research role with habilitation potential
• Structured mentoring and access to Talent Management programs
• An interdisciplinary and international working environment with close collaboration between AI experts and leading doctors
• Access to unique, large-scale medical datasets and high-performance computing infrastructure (including NVIDIA B300 GPUs)
• Funding for open-access publications and conference participation
• Support in developing your own research proposals
• Employee benefits: EGYM Wellpass, corporate discounts (eg, Käfer), and bike leasing (JobBike Bavaria)
• Free use of the library through a branch of the Munich City Library located in the building
• Working in the heart of Munich at Max-Weber-Platz with very good accessibility by public transport such as the subway, S-Bahn or tram
• Company pension plan through the Federal and State Pension Institute (VBL)
• Personal fulfillment through a varied and professionally demanding role with interdisciplinary collaboration

Requirements

• An outstanding doctoral degree (eg, magna cum laude or equivalent) in Computer Science, Medical Informatics, or a closely related field
• Proven track record in leading complex computer science projects and mentoring early-career researchers
• Documented expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture
• Strong Python programming skills and familiarity with machine learning frameworks (eg, PyTorch)
• Strong publication record and ability to communicate research results effectively
• A passion for tackling complex scientific challenges, a creative mindset for developing novel solutions, and a meticulous approach to research and validation
• A strong analytical and problem-solving mindset, with a keen interest in applying AI to solve complex challenges in personalized medicine
• Excellent communication skills in English; proficiency in German (at least B2 level) is required for project-internal and clinical collaboration

Check also:
2026 Fully Funded Humboldt Research Fellowship
2026 Konrad Adenauer Foundation Scholarship

Application Deadline

How To Apply

Contact:

• Maximilian Tschochehei, PhD, VIOLET Project, Institute for AI and Informatics in Medicine, Chair of Medical Informatics, Technical University of Munich (TUM), Ismaninger Str. 22, 81675 Munich
• Email: [email protected]

For more information, kindly visit TUM webpage.