Postdoc Markerless Motion Capture for Home Monitoring in Neurological Populations

Postdoc Markerless Motion Capture for Home Monitoring in Neurological Populations

Are you passionate about shaping the future of healthcare? Do you want to develop technology that truly matters in people’s lives? Join us in creating radical innovations that support patients at home

The BODIES group, at the department of Biomechanical Engineering TU Delft seeks a motivated postdoctoral researcher for a full-time, fully funded, 36-month project on privacy-preserving, single-camera markerless motion capture for clinical assessment and long-term home monitoring of motor impairments in stroke and Parkinson's disease patients. The position is based at TU Delft, with part of your time spent on-site at Model Health (Leuven, Belgium) for the development of the video-based prototype.

You will work closely with Model Health and Moveshelf, embedded in the multidisciplinary "Care is coming home!" program, a 5-year consortium of 2 technical universities (TU Delft, UTwente), 6 hospitals, 13 companies (including Model Health and Moveshelf), 1 rehabilitation centre, and 5 patient organisations.

The Challenge

Reliable, long-term monitoring of motor impairments outside the clinic is essential to support home-based rehabilitation, yet existing markerless motion capture systems are rarely validated on neurological gait patterns and struggle to generalize across pathology, body morphology, camera viewpoint, and home environments. This position aims to close that gap: you will develop and validate a novel single-camera markerless motion capture system, combining biomechanical realism, synthetic data generation, and privacy-preserving visualization within a single framework, to enable both clinical assessment and secure, long-term home monitoring.

• Validate the current markerless motion capture system against marker-based data in stroke patients
• Generate biomechanically accurate synthetic video data to expand training data and enable controlled sensitivity analyses across pathology severity, body morphology, camera viewpoint, and environmental conditions
• Develop a single-camera, home-based markerless system
• Test the algorithm across lab and home-recorded environments to assess real-world performance
• Design clinician-facing visualization tools ensuring privacy-by-design anonymization of patients and their home environment

You will translate this into a research plan aimed at peer-reviewed publications, alongside consortium deliverables.

Our offer

You will become part of the funded research program in the Netherlands named 'Care is coming home!', which involves 9 PhDs and 5 Postdocs. So, we offer an excellent inspiring, collaborative, and international research environment, with access to leading experts in medical technology and AI-driven healthcare solutions. Additionally, you will have access to state-of-the-art labs, clinical partners, and patient organisations, which are preconditions to make a meaningful contribution to the future of sustainable healthcare.

• Excellent mentorship and a stimulating international research environment with excellent facilities

We are seeking an ambitious, hands-on postdoctoral researcher who is excited to push the boundaries of markerless motion capture and its clinical application. You are eager to combine computer vision, biomechanics, and synthetic data generation to build tools that will shape the future of home-based rehabilitation monitoring.

You bring:

• A PhD in Biomechanical Engineering, Biomedical Engineering, Computer Vision, Robotics, or a related discipline.
• A strong curiosity for human movement analysis and markerless motion capture.
• Experience with pose estimation, computer vision, and/or synthetic data generation for model training.
• Solid programming skills (e.g., Python) for algorithm development, data analysis, and computational modeling.
• Experience with, or affinity for, clinical/experimental gait data from neurological populations (stroke, Parkinson's disease).
• Excellent organizational and communication skills to manage a multi-site project across academic and industry partners.
• Willingness to travel regularly to Model Health in Leuven, Belgium.
• Ability to work…