Musculoskeletal disorders, affecting muscles, bones, joints, and associated tissues, are the leading cause of disability worldwide. Musculoskeletal models hold great potential for prevention and development of new treatments, but current models often fail to capture sex diversity.
Our NWO Vidi Grant project, “Breaking BIASmechanics”, aims to create innovative technology for generating accurate musculoskeletal models outside the lab that account for sex variations. In collaboration with societal, industry, and health partners—including NOC*NSF, Vitronic, ModelHealth, and the Sport & Gyn network—these next‑generation models will allow us to explore how sex diversity affects movement and musculoskeletal loading, guiding more equitable rehabilitation, prevention, and performance programs.
The PhD candidate will serve as one of the modelling experts within the project team, focusing on developing methods to map internal musculoskeletal geometries from external body shape and demographics.
Responsibilities- Contribute to a large‑scale, multi‑year data collection effort with human subjects, using MR imaging, ultrasound, and motion capture
- Develop parametric models of the human body tailored to the demands of biomechanics research
- Design and train models to infer internal skeletal and muscular geometry from external body shape
- Build statistical models that capture validated relationships between individual musculoskeletal parameters to enable subject‑specific model personalisation
- Implement algorithms into hardware and software for 3D body scanning and video‑based motion capture
- Collaborate with an interdisciplinary team of experts in biomechanics, anatomy, medical imaging, clinical sciences, and sports coaching
- A Master's degree in Biomechanical Engineering, Biomedical Engineering, Technical Medicine, Applied Mathematics, Computer Science, or a related discipline
- Experience with statistical or parametric modelling (e.g. Statistical shape models, PCA‑based methods)
- Programming skills in Python, MATLAB, or similar
- Familiarity with musculoskeletal modelling (e.g. OpenSim, AnyBody, or similar)
- Affinity with biomechanics or human movement science
- Proficiency in English, both written and spoken
- The ability to work independently while thriving in a collaborative, multidisciplinary team
- Experience with medical imaging data (MRI, ultrasound, or CT)
- A background in machine learning or deep learning, particularly for regression or shape inference tasks
- Experience with 3D geometry, mesh processing, or computer vision
- Knowledge of motion capture systems or biomechanical data processing
- Ability to communicate with study participants in Dutch; knowledge of Arabic, Turkish, or other languages is an additional asset for participant inclusion
Doctoral candidates will be offered a 4‑year period of employment in principle, divided into two employment contracts: an initial 1.5‑year contract with a go/no‑go progress assessment within 15 months, followed by an additional contract for the remaining 2.5 years subject to performance requirements.
- Salary: €3,059 – €3,881 gross per month (based on the Collective Labour Agreement for Dutch Universities), increasing each year of the 4‑year period for a full‑time (38‑hour) contract
- Bonuses and allowances: 8 % holiday allowance and an end‑of‑year bonus of 8.3 %
- Additional benefits: health‑insurance discounts, a monthly work‑costs contribution, and flexible work schedules
- Enrolment in the TU Delft Graduate School and access to the Doctoral Education Programme teaching research skills
Documents to submit: CV and a motivational letter.
Applications must be received no later than 13 May 2026.
Language RequirementsEnglish proficiency at a level that allows participation in English‑taught doctoral courses, scientific writing, and oral communication is required.
EEO StatementApplicants from all backgrounds are encouraged to apply. Work environments are inclusive and offers fair consideration to all candidates.
Risk AssessmentAs part of knowledge security, TU Delft conducts a risk assessment during the recruitment process, based on information provided by candidates. This assessment is carried out on the legal basis of GDPR and is part of the public task in the public interest.
#J-18808-Ljbffr€3059 - €3881 monthly