The University of Twente in the Netherlands is offering a postdoctoral research position in the field of wearable robotics, biomechanics, and predictive control. The successful candidate will join the Neuromechanics and Neuromuscular Robotics Lab (NeuBotics Lab) led by Prof. Massimo Sartori, focusing on the development of real-time, AI-powered, model-based predictive control systems for robotic ankle exoskeletons. The research aims to enable closed-loop regulation of ankle muscle–tendon forces during human locomotion, integrating advanced musculoskeletal modelling, AI-based prediction (e.g., TCNN, LSTM), and model predictive control or reinforcement learning frameworks. The project involves developing and calibrating real-time musculoskeletal ankle models, combining AI-based prediction with these models to estimate and predict muscle activation and tendon force over short horizons, and validating the developed methods in human experiments using motion capture, electromyography, ultrasound, and dynamometry. The position is at the intersection of robotics, biomechanics, computer science, and AI, offering opportunities to collaborate with leading researchers across Europe and access to state-of-the-art lab and computational facilities. Applicants must have a PhD in Robotics, Control, Mechanical Engineering, Computer Science, or a related discipline, with experience in model predictive control, reinforcement learning, musculoskeletal or biomechanical modelling, control of wearable robots or exoskeletons, and real-time programming (C++, Python). Additional knowledge of real-time communication systems, closed-loop control, and experimental human movement data is advantageous. The position is fully funded for two years, with a possible 6-month extension, a competitive salary, generous allowances, and professional development opportunities. The application deadline is February 15, 2026. Interested candidates should apply online via the University of Twente careers platform, submitting a CV, motivation letter, a short video describing their scientific interests, and contact information for at least three academic references. For more information, contact Prof. Massimo Sartori at [email protected]. The University of Twente is a leading technical university with a vibrant international community and a strong focus on research at the interface of technology and human health.

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.

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.