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and imperfections, making them both conceptually deep and technologically promising. This theoretical PhD project will investigate how topology and quantum geometry emerge and intertwine such as
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High-order solvers offer clear accuracy advantages, yet their effectiveness is fundamentally limited by the availability of suitable high-order meshes for complex industrial geometries. Current
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advantages, yet their effectiveness is fundamentally limited by the availability of suitable high-order meshes for complex industrial geometries. Current workflows rely heavily on geometric de-featuring
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that respond dynamically to external forces. Such possibilities challenge conventional thinking in engineering and design. By studying how stresses, geometry, and material properties interact, we can develop
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, shocks, vortices, thermal gradients and structural stresses often occur in regions that are closely linked to the geometry of the problem. In current industrial workflows, these phenomena are commonly
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for many developments in model theory, starting with strong minimality, as well as providing some of the most important applications where model-theoretic tools are applied to algebraic geometry. After
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structural stresses often occur in regions that are closely linked to the geometry of the problem. In current industrial workflows, these phenomena are commonly captured either by globally over refining
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to complex geometries, and run in real time for digital-twin monitoring. This project will develop physics-informed Fourier Neural Operators (FNOs) for thermal NDE of curved and layered composite structures
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modelling framework to predict key thermal hydraulic parameters for boiling flows within complex geometries at high heat flux conditions, relevant to the engineering design of thermal management elements
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k Si3N4 and then the additive manufacturing of the components with the aim of achieving complex geometries with the enhanced ceramic. Funding notes: This PhD programme will be hosted in the School