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:
daniel.belavy@hs-bochum.de, Tel: +49 [(0)234 36186 9168).