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Advanced Carbon Fibre Composites using Next-Generation Additive Manufacturing (CFAM)
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Generalisable, Physics-Aware Machine Learning for Gas Turbine Engines
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in computational analysis of biological data Desirable Application/Interview Familiarity with nanoplasmonic sensing principles or surface functionalisation chemistry Desirable Application/Interview
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, Professor Jim Wild and the SPIRO investigators. The position sits within Work Package 4 (Technology Integration and Computational Analysis) of SPIRO, which is central to integrating and analysing data from
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subjected to a typical loading scenario. This research will benefit from excellent computing facilities, expertise in computer-aided engineering (CA2M lab), the available experimental facilities including
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Artificial intelligence and machine learning methods for model discovery in the social sciences
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computing facilities, expertise in computer-aided engineering (CA2M lab), the available experimental facilities including mechanical testing and links with industry and with our Advanced Manufacturing
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Computational Complexity Theory
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Design and Synthesis of Next-Generation High-Performance Energetic Materials
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Multi-Material Laser Powder Bed Fusion for Next-Generation Additive Manufacturing