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Vacancies PhD position on Dependability Driven on Device Learning Algorithms for Embedded Neuromorphic Architectures Key takeaways Edge devices that can learn autonomously while guaranteeing
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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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bioprinting, tissue culture, microfluidics, sensors and microscopy. In addition to this high-end equipment, the facility will develop unique wavefront shaping microscopes for imaging inside the complex culture
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to the full development pipeline: from algorithm design and implementation to clinical integration and evaluation. You will also work on improving prognostic models using (neuro-symbolic) AI and develop
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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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with established causal models. Ultimately, you will design algorithms for causality-based analysis and counterfactual recovery of liveness violations. Information and application Are you interested in