Professorship (W 2) in Data Science in Sports and Health

Organisation/Company Philipps-Universität Marburg-Ausschreibungen Department Personalabteilung Research Field Other Researcher Profile Established Researcher (R3) Positions Other Positions Application Deadline 8 Nov 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The professorship represents the field of Data Science in Sports and Health in both researchand teaching. It is conceived as a methodologically oriented cross-sectional professorship within Sport Science and Motology and is intended to ensure the sustainable integration ofdata science methodologies into the discipline. The focus lies on the development andapplication of innovative approaches in statistics, machine learning, and artificial intelligencefor data-driven decision support in the context of sports, movement, health, and medicine. The successful candidate is expected to pursue at least one of the following focal areas:

• Development and application of advanced methods for pattern recognition inmultimodal movement and health data (e.g. data derived from wearables, video,imaging, questionnaires, interviews, and clinical sources)
• Development and implementation of simulation and predictive models in sport, physicalactivity, and health, including preventive, rehabilitative and medical care contexts, aswell as applications involving augmented reality and visual analytics
• Development and application of edge and wearable computing technologies, encompassing real-time data analytics, algorithmic efficiency, and the validation of noninvasive measurement systems

Applicants must hold a completed university degree in sport science, mathematics, computer science, or a closely related discipline, have completed an outstanding doctoral degree, and demonstrate exceptional teaching aptitude. In addition, applicants are expected to have an internationally recognized expertise in data science, statistics, machine learning, or artificial intelligence, with a clear and documented focus on sport, physical activity, health, and medicine. This expertise should be evidenced by relevant international peer-reviewed publications and conference contributions. The successful candidate is expected to have a proven track record in securing competitive third-party funding, substantial experience in university-level teaching, and a strong record of interdisciplinary research and collaboration. Desirable qualifications include alignment with at least one research priority of the Department of Educational Science and Sports Science and one profile area of the Marburg University, as well as a demonstrated commitment to mentoring early career researchers. We also welcome active engagement in interdisciplinary and inter-institutional research consortia and a willingness to contribute to academic self-governance. Furthermore, the candidate should contribute strategically to the ongoing development of all degree programs within the Institute of Sport Science and Motology and be prepared to teach in English in both participating departments. The successful candidate will be expected to teach in German after a maximum of two years of employment. The employment requirements pursuant to §§ 67 and 68 of the HessHG. Marburg University places particular emphasis on intensive supervision of students and doctoral researchers and expects faculty members to maintain a strong and active presence on campus.

Specific Requirements

We support women and strongly encourage them to apply. In areas where women are underrepresented, female applicants will be preferred in case of equal qualifications. As a certified family-friendly university, we support our employees in balancing family and career. A reduction of working time is possible. as discribed in the Social Security Code (Section 2(2) and (3) of Book IX of the Social Security Code (SGB IX)) will be preferred in case of equal qualifications. Application and interview costs can not be refunded.

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