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on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order models, designing controllers that exploit
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analysis, focused on selected electrodes or brain regions. We would like to investigate how graph deep learning models can be designed to capture dynamics in brain signals for the accurate detection, and how
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outages and degradations become more severe. Technical failures, unplanned excessive load, design and implementation flaws in components, human error, and malicious intent all have the potential
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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Priority may be given to the following designated employment equity groups: women, Indigenous peoples* (First Nations, Inuit and Métis), persons with disabilities and racialized persons
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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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models, and reinforcement learning (RL), which is data-driven, are two powerful control techniques. MPC techniques are well-established, while RL techniques are gaining popularity due to increasingly
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curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical skills Multicultural and international work environment with more than 50
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preferably also of other languages. Anyone admitted who doesn’t have a command of Swedish will be expected to learn Swedish during the first two years of the Programme. Applicants will be assessed on the basis
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also design medical research experimental protocol for both healthy control population and target patient population, apply for the protocol’s ethical approval (please check this website for more