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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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international theoretical/computational partners. Your experience and ambitions Master’s degree in the field of condensed matter physics or a closely related field. Existing skills and knowledge in electronic
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas film flow within the microscopic seal gap. Couple CFD with Structural Models: Study the fluid-structure
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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modelling tools to understand and tailor the physical and chemical interactions at the interfaces within metascintillators. Cranfield University’s Centre for Materials is internationally recognised
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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both homogenous and heterogenous catalytic conversion, including the handling, testing and characterizing the catalysts as well as the reactor and process simulation and analysis. Details will be
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. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make