PhD students and Post-Docs for AI in medical imaging

Updated: about 2 months ago

26.05.2022, Wissenschaftliches Personal

The lab for Artificial Intelligence in Medicine at TU Munich is looking for several PhD students and post-docs to work on projects in the area of AI for medical imaging

The lab for Artificial Intelligence in Medicine, Institute for AI and Informatics in Medicine, focuses on AI and ML approaches for medicine and healthcare. We are based at the Klinikum rechts der Isar and Technical University of Munich (TUM). Our aim is to develop AI and ML techniques for the analysis and interpretation of biomedical data. The group focuses on pursuing blue-sky research, including:

  • AI for medical imaging applications ranging from image reconstruction to analysis and interpretation
  • AI for the early detection, prediction and diagnosis of diseases as well as for the identification of new biomarkers and targets for therapy
  • Safe, robust and interpretable AI approaches as well as as privacy-preserving AI approaches

We have particularly strong interest in the application of imaging and computing technology to improve the understanding of brain development, to improve the diagnosis and stratification of patients with dementia, stroke and traumatic brain injury as well as for the comprehensive diagnosis and management of patients with cardiovascular disease and cancer.

We are based in the Faculty of Medicine at the Campus Klinikum Rechts der Isar (which is the the university hospital of TUM) as well as in the Faculty of Informatics at the Campus Garching. Our lab is affiliated with several machine learning initiatives in Munich including the Munich Center for Machine Learning (MCML), the European Laboratory for Learning and Intelligent Systems (ELLIS Munich) and the Munich Data Science Institute (MDSI).

We are currently recruiting PhD students and post-docs to work on a number of projects including:

  • Deep learning based optical image reconstruction and analysis for real-time neuronavigation in brain surgery (Project Hyperprobe).
  • Development of predictive models using imaging, metabolic risk profile, and genetic data to help improve obesity prevention and treatment through personalized lifestyle recommendations ​​(Project ImaGENE).
  • Deep learning models for the integration of multimodal in vivo and ex-vivo imaging for the characterization of changes in the extracellular matrix of tissue and the identification of prognostic predictors for therapy (Project Matrix in Vision).
  • The development of robust AI models for medical imaging using sparse data, unlabelled data as well as noisy data (MCML-funded project).
  • Trustworthy AI for medical imaging, with a particular emphasis on the verification of AI models, the development of privacy-preserving AI approaches and the identification of biases in AI models (MCML-funded project).


  • For post-doc positions: A PhD in Computer Science or related disciplines and publications in medical imaging, computer vision or machine learning
  • For PhD positions: A MSc in Computer Science or related disciplines and publications and previous experience with projects in medical imaging, computer vision or machine learning
  • Strong background in medical image analysis and machine learning
  • Extensive programming experience with Python and Pytorch
  • Strong analytical and problem-solving skills
  • Excellent communication & interdisciplinary skills
  • Fluency in English (written and spoken)

Please send your application documents (CV, transcripts, and a two-page research statement) to by 17th June 2022.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.


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