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reduces computational cost and enables large-scale reactor simulations, current porous approaches, based on Reynolds-averaged Navier-Stokes models, rely on empirical correlations and assumptions that may
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us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of
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mechanics, acoustics, and computing science. It will potentially improve our current understanding of the silent flight of owls by uncovering the full mechanisms of noise reduction by flexible trailing edge
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molecular simulation) and the skills involved in using high-performance computing Continual interaction with an ongoing experimental program Introduction to chemical engineering design principles via flow
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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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physiology etc. This PhD project is suitable for applicants with a background in Electrical and Electronic Engineering or closely related fields. Candidates with a strong interest in RF engineering and/or
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Engineering and Analytical Science Civil Engineering Computer Science Electrical and Electronic Engineering Management of Projects in Engineering Mechanical Engineering Academic requirements To be considered
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where