Massimo Sartori

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.

This postdoctoral fellowship at the University of Twente offers an exciting opportunity to advance reinforcement learning for the control of human-inspired musculoskeletal robots. The position is part of a collaborative SNSF Co-Investigator Grant between ETH Zurich’s SoftRobotics Lab and University of Twente’s NeuBotics Lab, focusing on digital twins of musculoskeletal robots equipped with neuronal control networks. The project aims to derive robust robot controllers for sim2real applications, bridging robotics, biomechanics, artificial intelligence, and neuroscience. As a postdoctoral fellow, you will adapt human neuromusculoskeletal models to incorporate robotic limbs with muscle-like, variable-stiffness actuators. You will develop digital twins integrating neuromusculoskeletal and electrofluidic actuator models, and use reinforcement learning to train these twins for robust, human-like joint impedance control. The project also involves imitation learning frameworks, enabling robotic limbs to reproduce human movement and stiffness properties by observing human twins, and transferring RL-policies to real hardware. Secondary tasks include collaborating with interdisciplinary researchers in biomechanics, robotics, and machine learning, and disseminating research through publications, open-source software, and international conferences. The NeuBotics Lab is a multidisciplinary team at the forefront of neuromechanics, robotics, and human movement science, offering a dynamic research environment focused on translating computational models into real-world robotic applications such as prosthetic limbs, wearable exoskeletons, and autonomous musculoskeletal robots. Required qualifications include a PhD in Robotics, Computer Science, Artificial Intelligence, Control Engineering, Mechanical Engineering, Biomedical Engineering, Electrical Engineering, or a related discipline. Applicants should have a strong publication record in robotics, neuromechanics, reinforcement learning, or related fields, and hands-on experience with reinforcement learning, imitation learning, control of robotic systems, sim2real, machine learning frameworks (PyTorch or TensorFlow), GPU-accelerated simulation environments (MuJoCo, Newton), and programming in Python and/or C++. Excellent communication skills in English and the ability to work in an interdisciplinary environment are essential. Knowledge of soft robotics, electrofluidic actuators, prosthetic or assistive robotic technologies, and human movement analysis and biomechanics is a plus. The offer includes a full-time 2-year position (with possibility of 6-12 months extension), a gross monthly salary between €4241 and €4728 depending on education and experience, a 30% tax ruling option, pension scheme, annual holiday allowance of 8% of gross annual salary, end-of-year bonus of 8.3%, and a minimum of 41 holidays per year for full-time employment. The University of Twente provides excellent mentorship, professional and personal development programs, and access to state-of-the-art neuromechanics, robotics, and AI-compute facilities. The campus is located in Enschede, a mid-size city in the Twente region, offering a vibrant social environment and proximity to nature. Applications should be submitted via the University of Twente web platform by July 5, 2026. Required documents include a video describing your scientific interests, a cover letter detailing your experience and skills, a CV with English proficiency and publication list, and contact information for at least three academic references. For further information, contact Prof. Massimo Sartori at [email protected]. Please do not apply via email. The Faculty of Engineering Technology (ET) at University of Twente is committed to developing smart, sustainable, human-centred technological solutions for societal challenges, connecting education, research, and practice across core domains such as asset & maintenance engineering, intelligent manufacturing systems, personalised health technology, resilience engineering, and sustainable production, energy and resources. The open community fosters collaboration between students, researchers, staff, and industrial partners, driving innovation and impact.

Postdoctoral Fellow opening at the University of Twente in the NeuBotics Lab / Robotics Centre for research at the intersection of robotics , reinforcement learning , biomechanics , artificial intelligence , and control systems . The project is part of a collaborative Swiss National Science Foundation (SNSF) grant between ETH Zürich SoftRobotics Lab and the University of Twente . The research focuses on developing digital human twins of human-inspired musculoskeletal robots, combining neuromusculoskeletal modeling, reinforcement learning, imitation learning, and robotic experimentation to enable robust sim-to-real control. Research topics include adapting human neuromusculoskeletal models to robotic limbs, building digital musculoskeletal robot twins, training robot controllers with RL, learning human-like movement and stiffness through imitation learning, and transferring policies to real hardware. The role is especially relevant for candidates interested in soft robotics, muscle-like actuators, prosthetics, wearable exoskeletons, and adaptive robotic control. Eligibility highlights: a PhD in robotics, computer science, AI, control engineering, mechanical engineering, biomedical engineering, electrical engineering, or a related field; strong publication record; experience with RL/imitation learning, robotic control, sim2real, PyTorch/TensorFlow, GPU simulation environments such as MuJoCo or Newton, and Python/C++; strong English communication skills. Offer details: full-time 2-year postdoc with possible 6–12 month extension, salary €4,241–€4,728 gross per month, 30% tax ruling option, pension scheme, holiday allowance, end-of-year bonus, and generous leave. Deadline is 5 July 2026 . Interviews are planned for the week of 13 July 2026, with an expected start in October 2026 . How to apply: submit the application through the University of Twente web platform only. Required documents include a short video, cover letter, CV, and references. Email applications are not accepted.