Assistant Professor in Artificial Intelligence and Sensing Technologies for the Neuromuscular System
Are you passionate in science and ready to take a leadership role in your research career? Would you like to inspire the next generation of engineers? Are you looking to appoint your own PhD candidate and start up your own research group? The Biomechanical Engineering Department at the University of Twente is looking for an ambitious candidate to be appointed at the level of Assistant Professor. You will contribute to outstanding research and education activities in the broad area of Smart Sensing Technologies for the Human Neuromuscular System.
We seek exceptional candidates with proven expertise in combining wearable sensors with AI-data analytics. We seek candidates with expertise either at the software or hardware development levels. We look for applications combining AI and sensing to measure signals such as those related to the neural control of skeletal muscles, skeletal muscle mechanics, skeletal joint bending, etc., where such information is crucial and widely applied in scenarios such as personalized healthcare technologies, or musculoskeletal injury prevention, or assistive robotics, or human–machine interactions, or for the deeper understanding of human movement or neuro-rehabilitation processes. We’re looking for candidate with proven capacity to teach at BSc and MSc levels.
Areas of expertise may include (but are not limited to):
- Novel novel applications of wearable sensors and AI for personalized health care technologies.
- Development soft wearable sensing hardware for measurement of e.g., bio-electrical signals in neurons, nerves, and skeletal muscles as well as kinematics and kinetics measurement of skeletal muscles and body motions.
- Development of AI-algorithms for the extraction of information from networks of multi-modal sensors.
- Computational tools for speeding up AI-analytics from large sets of data.
- Continuous assessment of musculoskeletal health, technologies for collecting large-scale datasets, or AI-based prediction of injury risks or onset of degenerative disorders.
So, if you have original ideas on how to advance the development of AI-sensing technologies, please join our multidisciplinary and inclusive team.
The successful candidate will join the growing Chair of Neuromechanical Engineering, within which we bring forward our passion to interface the human neuromuscular system with robotic systems ultimately to enhance human health.
We are looking for someone who connects and strengthens our research and educational program on AI sensors but will bring complementary expertise to our group. The candidate is expected to participate in teaching, supervise students in their graduation assignments, and contribute towards the supervision of PhD candidates.
In this role you will have the opportunity to directly appoint your own PhD candidate, with the possibility to grow across the next Professorship stages e.g., Associate Professor. All your work takes place on the beautiful, green campus located in the Twente region.
Information and application
Apply by September 29th, 2023. Applications should include:
- A video (2-minute max) describing your scientific interests and why you are applying for this position.
- A cover letter (1-page max) specifying how your experience and skills match the position as well as summarizing your scientific work.
- A CV including English proficiency level, nationality, visa requirements, date of birth, experience overview, and publication list.
- Contact information for at least three academic references. A support letter will be requested by us only if your application is considered.
Incomplete applications will be discarded. Please, only apply via the University of Twente’s online portal (do not apply via email).
The first interview will take place in the week of October 9th., 2023.
The successful candidate will begin in early 2024.
For questions, please contact Prof. Massimo Sartori.
About the department
Chair of Neuromechanical Engineering
You will be working within our academic Chair, where we interface robotic technologies with the neuromuscular system to improve movement. We apply artificial intelligence, computational modelling, and biological signal processing, in a translational way, to develop novel real-time bio-inspired assistive technologies. Our goal is to establish a roadmap for discovering fundamental principles of movement at the interface between humans and wearable robots ultimately for improving human health. But we are always open to embrace new approaches! Together with industrial leaders and an extensive network of clinical institutions, we cover the entire trajectory from modelling a given subject population to the development of assistive robotics technologies. Our work is facilitated by the University's TechMed Centre, the Robotics Center and the Digital Society Institute.
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About the organisation
The Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first' university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.
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