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understand and characterise the real-world variability of conditions for chain drives in high performance sport. Improving the emulation of race conditions improves the optimisation of components for riders
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that deliver high power density and exceptional efficiency at reasonable cost. However, most existing machines, particularly high-speed, radial-flux permanent magnet motors, are reaching their performance
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alloys), and additive manufacturing to push performance boundaries. The research will seek optimal trade-offs between compactness and performance, delivering foundational insights into the future of high
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embrittlement. However, the immiscibility between Cu and W leads to poor bonding, whilst during high temperature manufacturing/operation embrittlement of steel-W joints occurs due to the formation of brittle
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platforms at both locations, providing the student with hands-on industrial experience as well as cutting-edge research insight. Description The global drive towards electrification in high-performance
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-Stokes equation are not eligible. Solving the BBGK equation is extremely challenging due to the high computational cost originated from its high-dimensionality. As a deterministic method, the potential
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that simulates real-world environmental conditions to test the durability and longevity of these materials and products made thereof, is also required. This PhD project aims to investigate novel high-performance
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-box techniques in the industry is still high. One of the main reasons is that the performance of such techniques highly depends on a large amount of good-quality data. Unfortunately, the availability
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Generative machine learning models have made significant progress in recent years. Typical examples include, for example, high-quality image or video generation using diffusion models (e.g
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in the USA. The main project for the student will be the computation of the properties of hadrons using lattice QCD and high performance computers. The PhD student will further investigate the use