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between process/system performance, reliability, energy and resource efficiency. This position offers unique opportunities with respect to high level research, training and innovation within manufacturing
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particular in deep learning, LLM, digital hardware design, embedded systems, audio processing; Proficiency in deep learning frameworks (e.g. PyTorch) and programming skills (SystemVerilog, Verilog, Python, C
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: Domestic students Study stage type: Future study Study area: Agricultural and veterinary sciences; Architecture, building, planning and design; Arts, humanities and social sciences; Business and economics
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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metres, including innovations in all that we do An environment encouraging curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical
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extrapolating loads along the substructure, for any type of turbine, given specific geometric, inflow and sea-state information. Furthermore, such a machine learning surrogate can speed-up both design and
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal