Publisher
source

Massimo Sartori

8 months ago

PhD Opening: Reinforcement Learning in Human Neuromusculoskeletal Models for Musculoskeletal Robot Control University of Twente in Netherlands

Degree Level

PhD

Field of study

Neuroscience

Funding

Full funding available

Deadline

Expired

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Country

Netherlands

University

University of Twente

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Keywords

Neuroscience
Computer Science
Biomedical Engineering
Mechanical Engineering
Motor Control
Reinforcement Learning
Mobile Robotics
Neuromuscular Physiology
Robotics
Tendon Biology
Biomechanic
Prosthetic

About this position

This PhD position at the University of Twente's NeuBotics Lab focuses on developing advanced computer models of the human neuromusculoskeletal (NMS) system for the control of human-inspired musculoskeletal robots. The project aims to combine detailed musculoskeletal geometries, muscle-tendon models, and neural control pathways (such as central pattern generators and reflexive mechanisms) to create large-scale, realistic simulations. A key aspect of the research involves designing novel reinforcement learning (RL) strategies to teach these NMS models to perform a wide range of movements, even in the presence of external disturbances.

The successful candidate will use the MyoSuite framework to develop and train NMS model control policies via RL, and will also work on transferring these learned policies from simulation to real-world robotic systems, including robotic legs and arms for both autonomous and prosthetic applications. Secondary tasks include applying these control policies to physical robots, contributing to the development of wearable exoskeletons and bionic limbs. The NeuBotics Lab is a multidisciplinary team at the forefront of neuromechanics and assistive robotics, bridging neuroscience, biomechanics, and robotics to create adaptive control strategies for real-time joint biomechanics.

The lab offers a collaborative and innovative environment, with strong connections to UT research institutes such as Mesa+ Institute, TechMed Center, and Digital Society Institute. Applicants are expected to have expertise in computer modeling, reinforcement learning, robotics, biomechanics, or related fields, and should be proficient in English. The application process requires a video, cover letter, CV, and references, with screening as part of the procedure. The deadline for applications is November 23, 2025, with interviews scheduled for the week of December 1, and the expected start date no later than February 1, 2025.

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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