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present with neurodevelopmental deficits associated with Autism Spectrum Disorder and hyperphagia, and in healthy controls. We will be using a range of methods, including behavioural phenotyping, cognitive
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, economic viability, and robustness to realistic operational uncertainty. PhD (or equivalent) in control engineering or closely related discipline. Track record in at least two areas: model predictive control
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Position Summary: Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering
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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
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AI approaches have recently been used to detect Alzheimer’s disease from CFPs among those with established disease (in case-control studies), the use of such approaches to predict disease (i.e., in
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candidate will contribute to feasibility studies on hybrid propulsion systems, the development of robust control architectures for autonomous docking, and predictive maintenance strategies using real-time
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of control theory and optimization. Knowledge of partial differential equations. Have a strong coding ability Research Associate: Hold a PhD in Engineering, Mathematics or a closely related discipline, or
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Applications are invited for one full-time EPSRC Industrial CASE (ICASE) PhD studentship for each project. “Development of natural-ageing-resistant, heat-treatable lean aluminium alloys
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will