Postdoctoral Researcher (E13 TV-L, 100%, m/f/d) in Machine Learning for Medical Image Analysis

Developing machine learning methodologies for medical image analysis with a focus on interpretability, robustness, or one of the other research areas of the group.

We invite applications for a fully-funded postdoctoral position in the Machine Learning in Medical Image Analysis (MLMIA) group led by Dr. Christian Baumgartner. The main research question we try to answer in the MLMIA group is “How can we bring machine learning technology to clinical medical imaging practice?”. Far from being solved, this question requires novel and creative approaches to numerous hard machine learning challenges. The main research focus of the MLMIA group is the development of methods that enable collaboration between humans and AI systems, in particular techniques for uncertainty quantification, interpretabiliy of predictions, and human-in-the-loop systems. A further focus is the application of generative modelling approaches to large medical imaging cohorts in order to better understand physiological and pathological processes and their connection to extraneous factors.

The successful candidate will be given the opportunity to shape their own research agenda within the confines of the group’s motivation.

What we are looking for

You have a strong academic background and hold a PhD in a quantitative discipline such as computer science, physics, mathematics, statistics, electrical engineering, or biomedical engineering. You are self-driven, curious, and enjoy analytical thinking. You have a strong motivation to do machine learning research as well as a keen interest to solve real-world clinical problems. Ideally, you have prior experience with machine learning, and strong programming skills in Python. Prior experience working with medical imaging data is a plus, but not required.

What we offer

The MLMIA group is located in the machine learning building of the University of Tübingen, together with the Cluster of Excellence “Machine Learning: New Perspectives for Science”, which the group is part of, and Tübingen AI Center. As such, the successful candidate will be embedded in an extraordinarily vibrant machine learning community in which regular exchanges of ideas and collaborations are common. The MLMIA group also greatly values the direct exchange with clinical partners from the University Hospital Tübingen.

About Tübingen

Tübingen is a scenic university town on the Neckar river in South-Western Germany. The quality of life is exceptionally high and the atmosphere is diverse, inclusive, and most locals speak English. Tübingen offers excellent research opportunities due to the University, four Max Planck institutes, the University Hospital, and Europe’s largest AI research consortium. You can find out more about Tübingen here:

How to apply

Please send a cover letter, your CV, copies of your university transcripts, and any additional information to support your application to Christian Baumgartner ( If you have any questions about the position, please do not hesitate to contact Christian directly. The university seeks to raise the number of women in research and teaching and therefore urges qualified women scientists to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen. Please submit your application by May 2nd, 2021.

Machine Learning in Medical Image Analysis
Machine Learning in Medical Image Analysis
Bridging the gap between AI and clinical practice