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this project, we aim to: Develop real-time ultrasound algorithms to estimate fascicle length in antagonistic leg muscles (tibialis anterior and soleus) in healthy individuals during walking. Translate and
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, spinal cord injury etc) through real-time neural control of wearable robotic exoskeletons. You will be developing next-generation (low and high-level) control algorithms for wearable exoskeletons that use
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The research will address key challenges and explore the following areas: 1. Decentralized Scheduling Algorithms: Design algorithms for operational scheduling and rescheduling of shared assets in connected
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of stroke patients and healthy volunteers. Developing algorithms for identifying and excluding motor unit filters associated to impaired motor units. Integrating real-time-decoded features of motor unit
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. For more information regarding this position, you are welcome to contact Prof. Wilfred G. van der Wiel via the following email address: W.G.vanderWiel@utwente.nl. Screening is part of the selection procedure
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application For more information about the position, you can contact Dr Caroline Gevaert (email: c.m.gevaert@utwente.nl) or Prof Raúl Zurita-Milla (email: r.zurita-milla@utwente.nl). You are also invited
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position, you are encouraged to contact Prof. Dr. Ir. Jimmy A. Faria (j.a.fariaalbanese@utwente.nl) Please apply via the button below. About the department The work will be carried out in the Catalytic
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of the processing system online. Our approach will be to draw on a broad selection of tools including (deep) reinforcement learning, queuing networks, online algorithms and systems engineering. In addition, a large
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AI models for network operations. This project is a joint effort between the University of Twente and TU Delft. You will be co-supervised by Associate Prof. Pedro P. Vergara from TU Delft and
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
with antennas, evaluate different algorithms for EM field strength data, investigating the minimal needed sensors (up to nine), and controlling the equipment using in-line measured data (closed-loop