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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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, drug formulations, gastrointestinal disorders and cell models, is highly desired. Funding Comment This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently
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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 project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable
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properties of cirrus, but we are currently limited by a lack of observational data. This project will fill that gap, using existing aircraft and satellite measurements to determine whether aircraft exhaust is
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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-on experience on SARRP and in vivo imaging modalities (CT, IVIS, ultrasound) Expertise in diet-induced fibrosis and surgical tumour models Image analysis, IHC, flow-cytometry Industrial experience with Xstrahl
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modelling capabilities for the prediction of energy extraction efficiency, especially focusing on improving the understanding and prediction of the complex flow phenomena, including buoyancy effects in AGS
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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