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).