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project will develop novel methods for modelling and controlling large space structures (LSSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. Working with leading
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existing biomedical foundation models (e.g., Med-PaLM) using techniques like Low-Rank Adaptation (LoRA). Big Data Analytics: Managing and analysing complex, multi-modal data from globally significant
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validate new capabilities within XCALibre.jl, Nottingham’s GPU-accelerated, AI-ready CFD framework, turning complex coupled physics into practical tools that engineers can use in real manufacturing workflows
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zone in a very complex manner and lead the modelling to an imperfect zone of assumptions. These complexities allow the researchers to use approximations for useful lifetime calculations. Based
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on particle complexity and surface roughness, using computational methods like physical optics and the discrete dipole approximation. Supervisors Entry requirements Applications are invited from individuals
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validate new capabilities within XCALibre.jl, Nottingham’s GPU-accelerated, AI-ready CFD framework, turning complex coupled physics into practical tools that engineers can use in real manufacturing workflows
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pollution, support biodiversity and deliver social value. Yet these trade-offs remain poorly quantified in complex urban landscapes. This PhD will investigate how urban blue networks can be optimised for both
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liquid methods, facilitating improved battery lifespan, reliability, and safety during ultra-fast charging and high discharge cycles. However, the multi-scale thermofluid dynamics complexities of boiling
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focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head
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architectures that are impractical for scenarios constrained by limited data and resources for fine-tuning and deployment of large-scale models. What’s more, multimodal models are particularly vulnerable to data