项目介绍

2026年4月30日

Are you looking to begin your academic career after completing your master’s degree and start a doctorate in artificial intelligence, medical informatics, and precision oncology? Then join the xMDT-HPB project at the Institute for AI and Informatics in Medicine (AIIM), a pioneering research initiative that is developing an explainable and interoperable multimodal AI system to improve personalized prognoses and treatment decisions for patients with hepato-pancreato-biliary cancers.

We integrate longitudinal clinical data, including medical text narratives, multimodal radiological imaging, and laboratory trajectories, to create AI systems that clinicians can understand and trust. All components will be released as open-source software and reusable research artifacts.

Your Responsibilities

You will work in an interdisciplinary team and build your scientific and technical skills in a structured manner. Your responsibilities will include in particular:

• Conducting your PhD within the xMDT-HPB project under structured academic supervision
• Familiarizing yourself with clinical data, medical research questions, and relevant standards such as MII / FHIR
• Contributing to the design, implementation, and documentation of research prototypes
• Developing and evaluating methods for explainable, multimodal AI systems, particularly for clinical text, imaging, and laboratory data
• Building and maintaining reproducible experiments, benchmarking pipelines, and analyses
• Collaborating with clinicians, data scientists, and software engineers to align requirements and validation scenarios
• Preparing research findings for internal project meetings, scientific publications, and conference contributions
• Contributing to open-source software, technical documentation, and quality assurance measures

Your Profile

• Completed academic university degree at master’s level in computer science, medical informatics, data science, bioinformatics, computational science, or a related field; a degree obtained by the planned start date is sufficient
• Commitment to pursuing a doctorate and conducting scientific work in an interdisciplinary medical-technical environment
• Solid programming skills in Python; initial experience with machine learning frameworks such as PyTorch or TensorFlow
• Initial practical experience from a master’s thesis, study projects, internships, or open-source projects in at least one of the following areas: machine learning, NLP/LLM, data analysis, software development, or medical data processing
• Willingness to familiarize yourself with medical standards, data protection requirements, reproducibility, and good scientific practice
• Careful, structured, and learning-oriented approach to work, along with a strong appreciation for teamwork and interdisciplinary communication
• Good written and spoken English; German language skills at least at level C1 are required for internal and clinical collaboration
• A brief overview of previous programming, data analysis, or machine learning projects; links to GitHub or GitLab are welcome
• If available: a list of publications, posters, thesis abstracts, or other academic evidence

What We Offer

• A fully funded doctoral position with clear onboarding, structured supervision, and regular academic feedback
• A scientifically ambitious project with high societal relevance, designed to build advanced research skills early in your academic career
• An interdisciplinary and international working environment at the intersection of AI research, medical informatics, and clinical care
• Support for scientific publications, open-access publications, and conference attendance
• Mentoring, qualification programs, and support in building an academic profile
• Contribution to open-source software and reusable research artifacts
• Remuneration according to TV-L EG 13 subject to personal and collective bargaining requirements, as well as occupational pension scheme via VBL
• Additional employer benefits, including EGYM Wellpass, Corporate Benefits, and access to the university library services
• Workplace in the heart of Munich at Max-Weber-Platz with excellent connections to subway, suburban train, and tram

Application

Please send your application as a single PDF to Dr. Felix Busch (felix.busch@tum.de). Your application should include the following documents:

• Motivation letter outlining your interest in pursuing a doctorate, AI, and medical informatics
• Curriculum vitae
• Certificates and transcripts from your bachelor’s and master’s degrees; if the master’s degree has not yet been completed, preliminary records are sufficient
• Brief overview of previous programming, data analysis, or machine learning projects; links to GitHub, GitLab, or similar platforms are optional
• If available: publication list, posters, thesis abstracts, or other scientific records
• Contact details of two academic references

Contact

Dr. med. Felix Busch
Chair of Medical Informatics
Institute for AI and Informatics in Medicine (AIIM)
TUM School of Medicine and Health
Ismaninger Str. 22, 81675 Munich
E-mail: felix.busch@tum.de

Applications will be reviewed on a rolling basis until the position is filled.