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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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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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be used effectively as a performance digital twin to generate high-quality engine performance models and produce required training data for the proposed project. This could be a good starting point for
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testing, enhancing both computational and experimental skills. Additionally, the possibility of contributing to cutting-edge research in a high-impact field means that the student will be part of a
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focus on studying the effects of high energy propagation in poor weather and investigate methods for increasing energy transfer on an intended object. The project will allow you to acquire expertise in
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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This PhD project offers a unique opportunity to delve into the complexities of free-market systems and sustainability through a novel ensemble prediction model. With a focus on addressing uncertainty and limited data availability, this research aims to revolutionize decision-making in...
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areas. Cranfield is part of the national testbed for 6G, researching in the following areas of interest: Real-time specification of 6G telecommunication and edge computing services using Large Language
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AI and ML are transforming electronics, automation, and intelligent systems, driving advancements in secure, high-performance, and adaptive technologies across industries. This self-funded MSc by
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material