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The project will prioritise digitising these records using natural language processing (NLP) and machine learning (ML) to create structured datasets. These will support AI applications in paediatric care
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Wales, meaning most paediatric records are handwritten and unstructured. The project will prioritise digitising these records using natural language processing (NLP) and machine learning (ML) to create
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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scheme eligibility are available on the UK Government website . ATAS clearance IS NOT required to be held as part of the scholarship application process. Successful award winners (as appropriate
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effects. The modelling technology will be leveraged to develop optimisation techniques for the operation of wind turbine arrays. The specific challenges will include understanding and modelling turbine
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, an expert-driven, manual, and time-consuming process used to simplify CAD models so that meshing tools can cope with small-scale features such as fillets and manufacturing details. This de-featuring is not
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language comes at a cognitive cost. Which begs the question: why do bilinguals choose to keep switching language types in conversation, despite apparent information processing inefficiencies? A phenomena we
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physical models. As the PhD researcher on this project, you will work at the intersection of machine learning, geometry processing and industrial simulation. You will have the opportunity to explore
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ATAS clearance. Further details on ATAS scheme eligibility are available on the UK Government website . ATAS clearance IS NOT required to be held as part of the scholarship application process
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defined by Swansea University) not holding a master’s degree, will be considered on an individual basis. Selection process Please see our website for further information. Website for additional job details