RESEARCH ASSOCIATE / DOCTORAL STUDENT (f/m/d) for the research Project "multidimensional analytic...

• 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 04.11.2026exclusively via our online application portal.
• We look forward to meeting you!

• For specific inquiries, please contact Prof. Dr. Daniel Belavy, E-mail:
• [email protected], Tel: +49 [(0)234 36186 9168).