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technical, economic, and social reasons. This leads to the need to integrate several new types of devices both at transmission and distribution level (e.g. renewable generation, HVDC interconnectors, electric
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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aligning with NQTP Missions 1 and 2 and NQCC Testbed programme, will tailor the developed benchmarking approaches to error-corrected as well as distributed quantum computers, addressing the need for scalable
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alongside traditional coal fired power stations and nuclear energy generation. Revolutionary changes to power conversion is indispensable if these carbon emissions targets are to be met. The objective is to
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, spanning domains from automotive and avionics to healthcare, increasingly rely on distributed and multi-layered control architectures. These systems comprise interconnected computing nodes, actuators and
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distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By establishing an understanding of "what normal looks like", these models will detect deviations from the norm and
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to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By
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. The temperature field generated by the interaction between the arc and the material plays a critical role in determining the microstructure, residual stress, and distortion of the built parts—all of which
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This PhD project will develop next-generation grid-scale energy storage solutions integrated into HVDC (High Voltage Direct Current) systems at the University of Edinburgh, in partnership with UK
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computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing