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Field
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty
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to participate in this collaborative research programme. They will be expected to contribute research to central datasets, and will be encouraged and supported to develop high-profile publications at the cutting
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design and situate research in broader literature. To use a realist approach to conduct semi-structured interviews to develop a programme theory to ascertain why, how, in what contexts, for whom and to
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Applications are invited for an EPSRC Industrial Doctoral Landscape Awards (IDLA) PhD position at the University of Nottingham addressing the specific engineering details of the wear of articulating
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. This correspondence is a cornerstone of the modern Langlands program, providing a deep and unforeseen bridge between harmonic analysis and number theory. The primary goal of this project is to formalise
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Specified use The awards are available on a competitive basis for candidates joining the PhD Accounting & Finance, PhD Business & Management or PhD Science, Technology & Innovation Policy programme at
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Application deadline: All year round This 3.5-year PhD project is fully funded; students who are eligible to pay tuition fees at the Home rate are eligible to apply (more details can be found here ). The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805...
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Location: Mechanical and Aerospace Systems Research Group, Faculty of Engineering, University of Nottingham Funding: UK Home fees + tax-free stipend of up to £25,000 p.a. for 4 years Applications
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within Oxford Population Health in the University of Oxford. We are seeking a Researcher from the Humanities/ Social Sciences disciplines, to join the Wellcome Trust funded discovery project After the end
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remain poorly understood. This fully funded PhD studentship offers an exceptional opportunity to work at the interface of health economics, behavioural science, and biological modelling to generate