RESEARCH ASSOCIATE / DOCTORAL STUDENT (f/m/d) for the research Project "multidimensional analytical approaches to improve LBP diagnosis and prognosis"
As a university of applied sciences, we are particularly committed to sustainable development. Based on our sustainability strategy, we integrate sustainability into all degree programs, applied research, and our daily operations. With our campuses in Bochum and Heiligenhaus, we provide important impulses for the regional development of society and the economy. Numerous collaborations underline our international focus. We aim to enhance the quality of our teaching and research by appointing further dedicated and innovative researchers.
In the Physiotherapy Division of the Department of Nursing, Midwifery and Therapy Sciences at Hochschule Bochum (Bochum University of Applied Sciences), a four-year position is available at the earliest possible date, and no later than March 2027, as
RESEARCH ASSOCIATE / DOCTORAL STUDENT (f/m/d) for the research Project "multidimensional analytical approaches to improve LBP diagnosis and prognosis" as part of the DFG Research Unit "DYN3M" (EG 13 TV-L)
The Project is funded by the German Research Foundation (DFG). The position is fixed-term for a period of 4 years for academic qualification, with a focus on multimodal data analysis in low back pain. Remuneration is paid in grade E13 TV-L, subject to the fulfillment of personal requirements. The working hours comprise 23 hours and 54 minutes per week (60% of a full-time position). As part of this project, a cooperative doctorate at the Doctoral School NRW (PK NRW) is envisaged.
The DFG-funded research project "DYN3M" (2026–2030) investigates the dynamic mechanisms of musculoskeletal health and the chronification of low back pain in order to drive the transition from generic treatment approaches to precise, personalized pain therapy. As part of your doctorate, you will work at the intersection of neuroscience, biomechanics, and data science to examine the interplay between the musculoskeletal system, neural movement control, and psychological factors. In doing so, you will apply machine learning and artificial intelligence methods to analyze multimodal data, identify high-dimensional signatures, and develop predictive models to evaluate whether individual healing trajectories exist and examing whether specific subgroups exist for targeted treatments to optimize overall therapeutic success.
Responsibilities:
- Project coordination and operational implementation of the project.
- In addition to project coordination with national and international partners, the project includes conducting subprojects as part of your doctorate.
- Learning and implementing quantitative data collection and analysis methods, including machine learning, as well as coordinating and drafting peer-reviewed publications.
- Participating in the development and application of state-of-the-art data science models in close collaboration with consortium partners from biomechanics, medicine, and psychology/psychosomatics.
- Presenting research findings at national and international conferences and symposia.
- Implementing modern data management standards and, where possible, open science publication of research outputs (metadata, analytical workflows, code, documentation, etc.) in compliance with the FAIR principles (Findable, Accessible, Interoperable, Reusable).
- Interdisciplinary collaboration within the research team.
Profile / Requirements:
- A completed university degree (Master's degree or an internationally equivalent degree) in physiotherapy, sports science, data science, statistics, medicine, health sciences, rehabilitation sciences, or a related field, as well as relevant research experience.
- Fulfilment of the formal criteria for enrolment as a doctoral candidate in the "Social Work and Health" department of the Doctoral College NRW (PK NRW) (see admission requirements of the Department of Social Work and Health at PK NRW) https://www.pknrw.de/abteilungen/soziales-und-gesundheit/gestaltung-des-sozialen-und-gesundheitlichen-wandels
- Very good written and spoken English skills (scientific communication) are required for the position; fluent German skills are not required.
- Experience collaborating in interdisciplinary teams.
- Proven experience in statistical analysis.
- Experience in machine learning and artificial intelligence is advantageous.
- Experience in project coordination, programming (e.g., R, Python), as well as in preparing scientific publications and grant applications is desirable.
What We Offer:
You will work in an interdisciplinary team dedicated to musculoskeletal health https://www.hochschule-bochum.de/forschung/ag-muskuskelletare-gesundheit/. You will receive comprehensive onboarding, benefit from flexible working hours, and have access to a modern environment to implement your ideas and projects. A home office component as part of the position is possible.
The position is classified under pay grade E13 of the Collective Agreement for the Public Service of the German States (TV-L).
Further information:
Based on our equal opportunity policy, we aim to increase the proportion of female researchers at our university and therefore particularly welcome applications from women.
Hochschule Bochum has been certified as a family-friendly university since April 2008. Applications from suitably qualified severely disabled persons or persons of equivalent status within the meaning of SGB IX are expressly encouraged.
Are you interested?
Then please apply by 04.11.2026 exclusively via our online application portal. We look forward to meeting you!
For specific inquiries, please contact Prof. Dr. Daniel Belavy, E-mail: daniel.belavy@hs-bochum.de, Tel: +49 [(0)234 36186 9168).