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Are you passionate about creating pioneering non-invasive techniques that could replace traditional invasive biopsies for assessing musculoskeletal health? Do you want to develop wearable systems for continuous, in-depth monitoring of skeletal muscle structure and inflammation over long timescales (months or more)? Are you ready to push the boundaries of muscle monitoring and machine learning to shape the future of rehabilitation and robotic training?
The Neuro-Mechanical Modeling and Engineering Lab (NMLab, http://bit.ly/NMLab) at the University of Twente invites applications for a 3-year postdoctoral position funded by the ERC Consolidator Grant ROBOREACTOR (https://cordis.europa.eu/project/id/101123866). This is an exciting opportunity to join a cutting-edge team at the intersection of neurophysiology, biomechanics, and rehabilitation robotics (http://bit.ly/NMLTube).
Project Overview
As a postdoctoral researcher in this project, you will work on breakthrough technology for non-invasive biopsies of skeletal muscles, specifically targeting the lower limbs. You will employ high-density electromyography (HD-EMG) and ultrasonography, combined with advanced statistical and machine learning techniques, to characterize muscle properties at multiple scales. Key focuses include:
Key Responsibilities
Apply by November 28th following the instructions outlined at this link: https://bit.ly/4evuJhv
The Neuro-Mechanical Modeling and Engineering Lab (NMLab, http://bit.ly/NMLab) at the University of Twente invites applications for a 3-year postdoctoral position funded by the ERC Consolidator Grant ROBOREACTOR (https://cordis.europa.eu/project/id/101123866). This is an exciting opportunity to join a cutting-edge team at the intersection of neurophysiology, biomechanics, and rehabilitation robotics (http://bit.ly/NMLTube).
Project Overview
As a postdoctoral researcher in this project, you will work on breakthrough technology for non-invasive biopsies of skeletal muscles, specifically targeting the lower limbs. You will employ high-density electromyography (HD-EMG) and ultrasonography, combined with advanced statistical and machine learning techniques, to characterize muscle properties at multiple scales. Key focuses include:
- Motor unit phenotype distribution
- 3D muscle fascicle morphology
- Muscle inflammation levels
Key Responsibilities
- Longitudinal Experimentation: Help conduct 12-week studies with both healthy participants and stroke patients.
- Advanced Muscle Monitoring: Use HD-EMG, ultrasound (USG), and force dynamometry in combination with machine learning to predict structural and inflammatory changes in muscle over time.
- Data Analysis: Set up robust HD-EMG and USG data repositories for analysis and model training.
- Validation: validate noninvasive biopsy results against reference data derived from invasive biopsies.
- Collaborative Innovation: Work with experts in robotics, control engineering, and muscle biology to develop robotic rehabilitation technologies for skeletal tissue regeneration.
Apply by November 28th following the instructions outlined at this link: https://bit.ly/4evuJhv