PhD Position in "Operator Surrogates for Model-Based AI"

The Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University is seeking a highly motivated PhD candidate in applied mathematics to join the Carl-Zeiss Foundation funded project “Model-Based AI: Physical Models and Deep Learning for Imaging and Cancer Treatment”.

The focus of the CZS Heidelberg Center for Model-Based AI is on developing methods for parameter inference in the context of medical imaging and cancer treatment. A key challenge in this area is to accurately and efficiently merge data with models in order to make accurate predictions and inform treatment decisions. To address this challenge, this subproject will explore the use of techniques such as low-rank tensor methods, sparse-polynomial methods, and operator surrogates to construct cheap and accurate surrogates for evaluating the underlying physical models. These surrogates will allow for faster and more efficient inference, enabling the development of more effective and personalized treatment strategies.

At Heidelberg University, we are committed to fostering a diverse and inclusive community. We encourage applications from women and individuals from underrepresented groups and strive to create a supportive and welcoming environment for all members of our community.

We welcome applicants with a Master’s degree in mathematics or a related field. To apply, please send a CV, transcript of records, and the names of two referees to Herta Fitzer at herta.fitzer@uni-heidelberg.de. For more details on the scientific part, please contact project supervisors Prof. Robert Scheichl (r.scheichl@uni-heidelberg.de) and JProf. Jakob Zech (jakob.zech@uni-heidelberg.de).