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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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comprehensive model of what tranquillity is, the factors that influence it and how to design for it. Attention to design contexts and design processes will be key to ensuring that useful measurements, methods and
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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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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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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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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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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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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