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interest in expanding their knowledge in both domains. (1) Geometry/Topology -related methods in computer science. (2) Machine Learning. (For example, graph neural networks, generative networks, or neural
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ultrafast laser pulses on femtosecond timescales. Combining nanofabrication, electromagnetic simulation, and pump–probe laser measurements, the project will explore how 3D geometry, and different materials
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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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to focus on the relationship between geometry and quantum theory. A key objective will be the conceptual and mathematical understanding of the original Penrose spin network, with a view toward foundational
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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their entire life cycle due to the variations arising from geometry, material properties and loads during the long-term operation. This leads to a growing need in model identification, calibration, and