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will focus on developing a bioinspired, AI-driven BCI system that enables intuitive and adaptive control of a wearable wrist-hand exoskeleton for stroke rehabilitation. The system will integrate
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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will develop in the position; it is expected that you have previous experience on each of them: Develop and implement CFD models to simulate the behavior of PRO systems. Apply ML algorithms to optimise