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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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, organisational and policy context of the National Health Service. The PhD research will focus on how bottom-up networks are involved in promoting change. In recent years, numerous networks of clinicians
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models for both industrial and environmental flows. Better predictions of these currents, particularly hazardous ones, will enable more effective mitigation strategies. The primary research method will be
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Engineering, Applied Mathematics, or Physics, is required from candidates. Desirable skills: mathematical modelling, numerical methods, good programming skills in any language, self-motivation and a passion for
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include: Theoretical modelling of nanoscale effects and processes in SNAP Development of experimental methods of picometre-precise fabrication of miniature optical devices at the surface of an optical fibre