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A leading university in Germany is seeking a motivated individual for a part-time research position in the Ankle ReLoad project. This role focuses on developing a wearable measurement system for ankle rehabilitation, involving movement analysis and machine learning. Ideal candidates will have a Master's degree and strong programming skills. The position offers a chance for international collaboration and contributions to scientific publications, alongside numerous benefits including flexibility and support for employees with family responsibilities.
42,500 students and 7,750 employees in teaching, research and administration, all working together to shape perspectives for the future – that is the University of Münster. Embedded in the vibrant atmosphere of Münster with its high standard of living, the University’s diverse research profile and attractive study programmes draw students and researchers throughout Germany and from around the world.
The Institute of Sport and Exercise Science in the Faculty of Psychology and Sport Science at the University of Münster, Germany, is seeking to fill the position of a
for the externally funded project Ankle ReLoad commencing on 1 April 2026. We are offering a fixed-term part-time position (80%) for 3 years and 5 month.
Project background
Every year, approximately 105,000 patients in Germany and the Netherlands are treated for ankle fractures, most of them between 35 and 65 years old. In addition to the personal impact, these injuries lead to considerable societal costs due to lost workdays. Clinical evidence shows that active ankle joint loading significantly improves recovery. However, the optimal loading intensity is still unknown: excessive loading may delay healing, while insufficient loading limits functional recovery.
The Interreg collaboration project Ankle ReLoad aims to develop a wearable measurement system capable of assessing ankle joint loading in home-based rehabilitation using a minimal number of sensors. High‑precision laboratory measurements of full‑body movement and external forces will serve as the foundation for training predictive models. Using machine learning, these models will estimate joint loads from wearable sensor data and provide personalised feedback to patients and clinicians via a digital application.
You will work at the interface of movement analysis, biomechanical modelling, software development, and AI‑based data analysis, collaborating closely with engineers, movement scientists, and clinicians. Your responsibilities include technical support for experiments, integrating recorded signals into the musculoskeletal model Myonardo, and calculating body loads. You will develop a database for storing and sharing measured and processed data. In addition, you will work with machine‑learning developers to implement body‑load prediction algorithms into the musculoskeletal model.
We offer:
The University of Münster strongly supports equal opportunity and diversity. We welcome all applicants regardless of sex, nationality, ethnic or social background, religion or worldview, disability, age, sexual orientation or gender identity. We are committed to creating family‑friendly working conditions.
We actively encourage applications by women. Women with equivalent qualifications and academic achievements will be preferentially considered unless these are outweighed by reasons which necessitate the selection of another candidate.
Are you interested? Then we look forward to receiving your application by 2026-01-02 at:
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