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of Sheffield. The role is part of a programme of research that is fully funded by the Aerospace Technology Institute (ATI) in a large collaborative programme with several Industry partners, including Airbus
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Low maintenance reliable main bearings for large wind turbines Offshore Wind CDT PhD Research Project Competition Funded UK Students Prof R Dwyer-Joyce, Dr Gary Nicholas, Mr Wooyong Song
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large research portfolio, it has extensive experimental, computational modelling and prototyping facilities. The candidate will benefit from working within a large, multi-disciplinary research group, and
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to handle constraints and optimize the performance or economy of the system. One of the main barriers to adoption of MPC for power system control (and, indeed, large-scale systems in general) is its
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science, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
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themes of “digital research”. The research elements of the post will include the application of big data approaches, artificial intelligence and machine learning to neurodegenerative disease drug design or
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Rethinking scholarly and editorial practices for born-digital data Digital Humanities Institute PhD Research Project Self Funded Dr Isabella Magni Application Deadline: Applications accepted all
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healthcare technology. Project Overview Healthcare digital twins are virtual replicas that continuously assimilate patient data to provide personalised predictions and support clinical decisions. To enable
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further information about the group’s work and publications at http://osbornelab.group.shef.ac.uk. Enquiries should be directed to Colin Osborne c.p.osborne@sheffield.ac.uk. Funding Notes First class or
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limited to machine learning, Natural Language Processing, large language models, data visualisations, and linked open data, can help streamline and improve editorial workflows. At the same time, it