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Massimo Sartori

6 months ago

Postdoctoral Researcher in Predictive Control of Leg Muscle Dynamics via Wearable Exoskeletons University of Twente in Netherlands

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Expired

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Country

Netherlands

University

University of Twente

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Keywords

Computer Science
Biomedical Engineering
Mechanical Engineering
Electromyography
Reinforcement Learning
Musculoskeletal Biology
Motion Capture
Model Predictive Control
Robotics
Human Movement

About this position

The University of Twente invites applications for a postdoctoral researcher to join a cutting-edge project focused on the predictive control of leg muscle dynamics via wearable exoskeletons. This position is situated at the intersection of musculoskeletal biomechanics, artificial intelligence, and real-time robotic control, offering a unique opportunity to advance the field of human-robot interaction.

The successful candidate will develop and calibrate real-time musculoskeletal ankle models, with a particular emphasis on the Achilles tendon, using advanced tools such as CEINMS-RT. The research will integrate AI-based prediction methods (including TCNN, LSTM, and others) with musculoskeletal models to estimate and predict muscle activation and tendon force over short time horizons (approximately 200 ms). These predictions will be incorporated into model-predictive control (MPC) or reinforcement learning (RL) frameworks to compute optimal exoskeleton assistance in real time. The developed methods will be validated through human experiments utilizing motion capture, electromyography, ultrasound, and dynamometry.

Applicants should hold a PhD in Robotics, Control, Mechanical Engineering, Computer Science, or a related discipline. Essential experience includes model predictive control and/or reinforcement learning, musculoskeletal or biomechanical modelling, control of wearable robots or exoskeletons, and real-time programming (C++ or Python). Additional desirable skills include knowledge of real-time communication systems (such as EtherCAT or CAN bus), closed-loop control of robotic systems, and experience with experimental human movement data (EMG, ultrasound, motion capture). The ideal candidate is creative, proactive, and comfortable working at the interface of AI, physics-based modelling, and control.

The position offers a full-time, 2-year contract with the possibility of a 6-month extension. The salary ranges from €4241 to €4412 per month, depending on experience, and includes a 30% tax ruling option, a comprehensive pension scheme, an 8% holiday allowance, an 8.3% end-of-year bonus, and a minimum of 29 holidays. The University of Twente provides access to state-of-the-art neuromechanics, robotics, and AI-compute facilities, as well as professional and personal development programs. The campus offers a vibrant international scientific community, free access to sports facilities, and a green environment near the city of Enschede.

Applications must be submitted via the University of Twente web platform by February 15, 2026. Required documents include a 2-minute video describing your scientific interests and motivation, a 1-page cover letter detailing your relevant experience, a CV with English proficiency, nationality, visa requirements, date of birth, experience overview, and publication list, and contact information for at least three academic references. For further information, contact Prof. Massimo Sartori at [email protected]. Please note that applications via email will not be considered.

This is an excellent opportunity to contribute to innovative research in predictive control, biomechanics, and wearable robotics at one of the Netherlands’ leading technical universities.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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