Post-doc Opening: Predictive Control of Leg Muscle Dynamics via Wearable Exoskeletons
Are you passionate about creating next-generation wearable exoskeletons that can actively regulate muscle-tendon loading and prevent musculoskeletal injury risk? Are you interested in developing predictive, closed-loop control strategies that combine artificial intelligence, real-time musculoskeletal modelling, and model predictive control, operating at the time scale of human neuromuscular dynamics (milliseconds)?
We are seeking for a highly motivated postdoctoral researcher to develop real-time, predictive control frameworks for ankle exoskeletons that regulate calf muscle-tendon forces during human locomotion. A central goal is the short-term (millisecond-scale) estimation and prediction of muscle activation and tendon force over a prediction horizon (e.g., 200 ms), with validation using ultrasound measurements of the Achilles tendon. The position is at the intersection of musculoskeletal biomechanics, AI-based prediction, and real-time exoskeleton control.
Research Focus
The successful candidate will work on the development of predictive, real-time control frameworks for ankle exoskeletons that regulate muscle–tendon forces during locomotion.
This includes:
- Developing and calibrating real-time musculoskeletal ankle models (using CEINMS-RT), with emphasis on the Achilles tendon.
- Combining AI-based prediction (e.g., TCNN, LSTM, etc) with musculoskeletal models to estimate and predict muscle activation and tendon force over short horizons (e.g. ~200 ms).
- Integrating these predictions into model-predictive control (MPC) or reinforcement learning (RL) frameworks to compute optimal exoskeleton assistance in real time.
- Validating the developed methods in human experiments using motion capture, electromyography, ultrasound, and dynamometry.
Your Tasks:
- Developing and validating subject-specific musculoskeletal ankle models.
- Combining AI-based prediction with MSK models for real-time muscle-tendon force estimation.
- Designing predictive control strategies that regulate muscle-tendon loading via wearable exoskeletons.
- Implementing and testing control algorithms in simulation and real-time settings.
Information and application
Apply by 23:59 on February the 15th, 2026. Interviews will take place in the week of March 9th. Expected starting date is May 2026. Applications should include the following documents:
- A video (2-minute max) describing your scientific interests and why you are applying for this position.
- A cover letter (1-page max) specifying how your experience and skills match the position as well as summarizing your scientific work.
- A CV including English proficiency level, nationality, visa requirements, date of birth, experience overview, and publication list.
- Contact information for at least three academic references. A support letter will be requested by us only if your application is considered
Screening is part of the procedure.
For more information on the open position, you can contact Prof. Massimo Sartori, mail: m.sartori@utwente.nl. Please, only apply via the web platform. Please, do not apply via email.
About the organisation
The Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first' university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.
Want to know more
