15.10.2024

Postdoctoral Researcher and Coordinator of Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” (m/f/d, E13 TV-L)

Faculty of Science, Department of Computer Science

Application deadline: 15.11.2024

The University of Tübingen is a leading place for research in artificial intelligence with excellent research infrastructure and the University Hospital Tübingen offers a combination of high-performance medicine and strong research.
The goal of the Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” is to enable the beneficial use of ML in healthcare through research in the foundations of safe ML-systems and the development of protocols and automatic tools for their certification.

Tasks and responsibilities

• Research in an area of safe machine learning and/or applications in healthcare
• Management of a team of PhD students, postdocs, and software developers
• Coordination of the implementation of research prototypes in different healthcare domains in our “AI Safety Test Bench”
• Coordination with our project partners
• The position is limited to 3 years

Your Profile

• PhD degree in computer science or a related field
• Research profile in machine learning (e.g. robustness, out-of-distribution/anomaly detection, fairness, explainability, uncertainty quantification) or AI applications in the healthcare domain
• Interest in safe machine learning and its certification, and implementation of regulation frameworks like the EU AI Act, General Data Protection Regulation (GDPR) and the Medical Devices Regulation (MDR)
• Very good coding skills, experience in managing and development of software projects is a plus

Your application

Please send your application (including a motivation letter, your CV, up to two representative publications, and the contact information of two referees as a single PDF) to Patrizia Balloch at safe-ml-sysspam prevention@inf.uni-tuebingen.de. The deadline for applications is November 15th, 2024.

For further information about the position contact Prof. Matthias Hein at matthias.heinspam prevention@uni-tuebingen.de