As part of its strategic planning, the University Medical Center Göttingen (UMG) is pursuing the consistent further development of its profile-forming research focus on neurosciences, cardiovascular medicine and oncology with translational approaches, including as a partner site of the health research centers German Center for Cardiovascular Research (DZHK), German Center for Neurodegenerative Diseases (DZNE) and German Center for Child and Adolescent Health (DZKJ). The UMG is closely networking on the Göttingen Campus with the natural and life sciences institutions of the university as well as the non-university institutions on site.
The Institute for Occupational, Social and Preventive Medicine ( at the University Medical Centre Göttingen (UMG) studies modern working environments in a digital society. The institute focuses particularly on societal, industrial and corporate transformation processes, digitalization, and the use of artificial intelligence (AI) to promote health and safety in the workplace. The Institute for Occupational, Social and Preventive Medicine at UMG is under new management since the end of 2024. It is part of UMG's healthcare research division and specializes in AI-supported research approaches. To further develop this area of expertise,
University professorship
(m/f/d)
in 'AI in Occupational, Social, and Preventive Medicine'
(salary grade W2)
will be filled on a permanent basis as soon as possible.
The institute maintains close ties with other scientific institutions and faculties at the UMG, as well as transregional initiatives such as the Campus Institute for Data Science (CIDAS), the Medical Data Science Section (MeDaS) and the Lower Saxony Centre for AI and Causal Methods in Medicine (CAIMed). Collaborations with major international companies, including Volkswagen AG, provide access to extensive and diverse datasets for research purposes.
The successful candidate will play a pivotal role in representing the field of AI within the context of occupational, social, and preventive medicine, both in research and teaching. The candidate will collaborate closely with the Head of Department to advance this field. The integration of AI into occupational and social medicine is still in its infancy. Active development of this integration is essential for the future of research, practice and teaching in these fields.
Your tasks:
* Establishing the research focus of 'AI in occupational, social and preventive medicine'
* Attracting third-party funded research projects
* Involvement in executing existing teaching duties, conceptualizing new courses with a focus on AI and supervising students
* Academic administration tasks
* Foundational research into AI and causal methods, such as developing, investigating and applying methods for causal inference, and evaluating artificial intelligence.
* Further development of predictive systems in the context of health; visualization of complex relationships; image and video analysis; and pattern recognition.
* Development, validation and implementation of AI algorithms and tools for analyzing and predicting health-related events, process optimization and decision support in healthcare.
* Validation of models to ensure accuracy and reliability.
* Evaluation of large datasets (big data), for example from health insurance companies or large corporations, in the context of health and prevention.
Requirement profile:
* A relevant academic degree (e.g. in statistics, computer science, AI, epidemiology, mathematics or data science)
* Outstanding PhD in statistics, mathematics, AI or a related subject with strong quantitative components
* Independent scientific work in the field of AI, statistics or data science after completing a PhD
* Experience in developing and applying methods for causal inference and evaluating artificial intelligence, preferably in a medical context
* Knowledge of database technologies and big data
* Experience in acquiring third-party funding and in interdisciplinary research collaborations.
* Experience in teaching and academic self-administration
* Language skills (CEFR level): At least C1 level English
* Additionally, knowledge in the field of health data and digital health systems is an advantage
* Language skills (CEFR level): English at least C1
* Knowledge of health data and systems is an advantage
Further requirements for the appointment of university professors are laid out in the current version of § 25 of the Higher Education Act of the State of Lower Saxony (Niedersächsisches Hochschulgesetz). The UMG reserves the right of appointment.
Applications from scientists from abroad are explicitly welcome.
The UMG aims to increase the proportion of women and therefore expressly encourages qualified women to apply. Severely disabled persons will be given preferential consideration if suitable.
Please submit your application documents online at by 12 th November 2025 at the latest.
If you have any questions, please contact us at berufungsportal@med.uni-goettingen.de