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Research theme: “Groundwater remediation”, “Environmental application of nanotechnology”, “Groundwater modelling”, “Aquifer”, “MODFLOW model”, “Nanoparticle transport in porous media”, “Nanoparticle
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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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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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PhD Studentship: Knowledge models for healthcare digital twins and improved patient care pathways School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded Students
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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
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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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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