Postdoctoral Researcher in Trustworthy AI in Medicine
Technical University of Munich Institute for Artificial Intelligence and Informatics in Medicine

Postdoctoral Researcher in Trustworthy AI in Medicine

09.12.2021, Wissenschaftliches Personal

The Technical University of Munich is one of Europe’s leading higher education institutions and has consistently been awarded high ranks in worldwide assessments.

The Institute for Artificial Intelligence and Informatics in Medicine, founded in 2020, is a vibrant and diverse academic team collaborating and innovating in computational research for AI applications in medicine and medical imaging.

Among our main areas of interest is trustworthy machine learning in medicine and healthcare, especially explainability, uncertainty quantification, causality and privacy. We are looking for an outstanding Postdoctoral Researcher to join our team.

Your Duties and Responsibilities You will perform cutting-edge research on novel Trustworthy Artificial Intelligence (AI) / Machine Learning ML methodology, theory and applications with a clear focus on robust, reliable and scalable technologies for clinical translation. You will work in one of the following areas:

  • Interpretable and explainable AI/ML
  • Privacy-preserving AI, especially differential privacy and distributed machine learning
  • Uncertainty quantification and Bayesian deep learning
  • Machine learning foundations

In addition, you will apply the developed techniques to biomedical data, in particular biomedical imaging.

Essential Requirements

  • A PhD (or equivalent) in an area pertinent to the subject, e.g. in machine learning, mathematics, cryptography or electrical engineering
  • A strong background in mathematics and machine learning/ artificial intelligence
  • Experience with working with biomedical data, e.g. medical imaging
  • Excellent programming skills, at the very least in Python
  • Practical experience within a multi-disciplinary research environment
  • Excellent oral and written communication skills and a strong publication track record in relevant conferences and/or journals
  • Ability to prioritise work to meet deadlines, supervise team members and work autonomously to reach common goals

Further Information Please provide the following documents:

  • A full CV including publications
  • A two-page research statement indicating your area of interest and why your expertise is relevant

For any enquiries, please contact Professor Daniel Rueckert,

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