Assistant Professor (Tenure Track) in Health Data Science

In this role, you will be responsible for the development of an innovative research agenda and teaching offers in the domain of quantitative methods and data science at the Faculty of Health Sciences and Medicine. You will promote research in the faculty and at the national and international levels, actively participate in teaching in the faculty's degree programs, and engage in the promotion of young academics.

The successful candidate will have a PhD in mathematics, statistics, epidemiology, econometrics, or a related discipline with a specialization in data science. A main focus of the position is on research and analysis of big data in healthcare, ideally using experimental and quasi-experimental research designs for generating new insights, the application of causal machine learning methods, and further developments of statistical methods in the domain of data science. We expect applicants to have a relevant track record of publications in their field, proven teaching experience, and evidence of competitively obtained research funding.

Important for this position is a high degree of integration ability, willingness to cooperate, and sense of higher-level goals. The willingness to provide methodological advice and to establish and maintain new research collaborations are essential prerequisites for the position. The Faculty of Health Sciences and Medicine is interdisciplinary. Therefore, beyond the subject-specific requirements, competencies in interdisciplinary teaching and research across all areas represented in the faculty are desired. The ability to work in a team and the willingness to contribute to the continuous development of the faculty are expected.

We offer an inspiring working environment at a young and dynamic faculty, optimal conditions for personal development, and a place of work with a high quality of life.

German language skills are an advantage but not required.