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4-year D.Phil. studentship Supervisors: Dr Simone Falco, Prof Daniel Eakins Classic finite elements approach (FEA) approximate the shape of the model using elements with planar faces, therefore
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the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid. We expect the stipend to increase each year. Generative models, such as large language models (LLMs), have exhibited remarkable success in
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This PhD scholarship is for candidates interested in developing culturally inclusive AI by creating methods and datasets to align large language models with global social and legal norms. This PhD
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the transition to a full-time training model, and how these demands can be best managed to maximise adaptations and performance, and mitigate injury risk. The successful candidate will audit the current scientific
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In this PhD project, we will develop and implement approaches for estimating the uncertainty in AI predictions of chemical reactivity, to help strengthen the interaction between human chemists and machine learning algorithms and to assess when AI predictions are likely to be correct and when,...
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health with the aim of creating healthier spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based
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to develop a simple and reproducible cell-based model to investigate how the changes in blood flow associated with pre-eclampsia damage the syncytiotrophoblasts leading to the detrimental release of factors
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materials. The computer modelling of LSP remains challenging due to its multi-physics and multi-scale nature. The dependency of the process on the shape of the laser pulse, its energy, ablation layers etc. is
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- Model-based assessment of climate impacts on conflicting land use systems Reference code: 50139755_2 Commencement date: August 1st, 2025 Work location: Hamburg Application deadline: 04.06.2025 The Climate
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The University of Exeter and Oxford Instruments Plasma Technologies are offering a jointly funded PhD position in computational and machine learning modelling of low temperature plasmas. Oxford