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of developing novel computational frameworks that seamlessly integrate machine learning techniques with established methods in computational mechanics, such as the Phase-field Finite Element Methods. Potential
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The Japanese Long-Baseline Neutrino Programme (T2K, Super-Kamiokande and Hyper-Kamiokande) School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr S Cartwright, Dr Patrick
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engineers to monitor and maintain shell structures in real time. By combining data from sensors with advanced computer models, a digital twin can continuously track how a shell responds to changing loads and
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methods for circular buildings, testing these on building data available at planning stage, and at a construction stage, to produce a critique of existing methods. These methods will then be developed and
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Familiarity with numerical simulations of nano-photonic structures. Desirable Application/interview Familiarity with semiconductor nano-fabrication methods and understanding of nano-scale characterization
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at the University of Sheffield. Single photons are the indispensable information carriers for core quantum technologies, including quantum communication and computation. The critical hurdle is the reliable
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at the intersection of molecular biology, computational science, and translational oncology, contributing to cutting edge research in the pathology of head and neck cancers. Led by Professor Ali Khurram
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Shifting bits: Adaptive numerical precision for GPU software in particle physics and beyond (S3.5-COM-Richmond)
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is on mathematics and computation. At the heart of the project are value-based decision problems. Here, an agent receives noisy information about the value of several possible options. The agent must
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this challenge by: • Applying innovative methods for visualising actin filament architecture using advanced imaging modalities (e.g., super-resolution microscopy) • Developing computational approaches