The Medical Faculty of Ulm University, is seeking to fill the position, starting as soon as possible, of a
Professor (W3) for Artificial Intelligence (AI) in Medicine
management responsibilities (f/m/d)
Ulm University has unique expertise in the research areas of trauma, ageing, oncology, and neurology, supported by three Collaborative Research Centres and specialized centers dedicated to these topics. As an active participant in the German Medical Informatics Initiative and the Network of University Medicine (NUM), we have access to numerous biomedical databases. Ulm University offers a range of cutting-edge Medicine and STEM programs, some of which are taught in English. Our dynamic academic environment fosters innovation and cross-faculty collaboration to tackle complex challenges in areas such as life sciences, artificial intelligence (AI), and quantum technology.
With this professorship, we aim to further strengthen our existing research structures by addressing translational biomedical questions through AI and machine learning (ML).
We are seeking an outstanding individual to lead and establish an internationally visible Institute for AI in Medicine, focusing on the application and development of AI methodologies for analyzing biomedical datasets. The ideal candidate will have a distinguished track record and a strong network of collaborations in AI for medicine, encompassing areas such as multiomics, imaging, or the integration of complex medical data. The candidate is expected to contribute to both curricular and extracurricular teaching in Medicine and STEM programs including molecular medicine, computer sciences, and technology, as well as to develop new academic programs.
Employment requirements are completed university studies as well as teaching aptitude, a doctoral degree and further pertinent scientific achievements (§ 47 LHG).
Your contact for further information: Prof. Dr. Markus Huber-Lang, Vice Dean, Tel. +49 731 50-54800
Application deadline: 23.03.2025
The University is seeking to increase the proportion of women in research and teaching and particularly encourage qualified female scientists to apply for this position. Severely disabled applicants with equal aptitude will be given preferential consideration.