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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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Area Engineering Location UK Other Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and
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This PhD project will focus on developing AI-based methods to accelerate the Swansea University in-house discontinuous Galerkin (DG) finite element solver for the Boltzmann-BGK (BBGK) equation
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environment. Even smaller pieces pose the potential to damage and further fragment active satellites and larger space debris, endangering current satellite operations and accelerating the proliferation of space
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of the training data. Hardware vendors have begun to design specialised hardware accelerators that can perform very efficiently a limited range of operations using low-precision formats such as FP8, binary16
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digital twins, and life cycle assessment (LCA). A central component of the research will be the development of digital twins to simulate the entire production process, from raw materials to final product
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deep generative models, e.g., diffusion, energy based, normalizing flow or transformer-based models. With a focus on the particular domain of molecules. The project will contribute to accelerate the drug
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deep generative models, e.g., diffusion, energy based, normalizing flow or transformer-based models. With a focus on the particular domain of molecules. The project will contribute to accelerate the drug
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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Bandgap Semiconductor Device Technology) to accelerate the UK’s ambition for NetZero by transforming the next generation of high voltage electronic devices using wide/ultra-wide bandgap (WBG/UWBG) compound