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? Are you looking for a new and exciting challenge to develop innovative digital tools combining CFD and machine learning to reduce manufacturing-induced deficiencies of ceramics? We have a vacancy for an
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Analysis of post-combustion CO2 capture from natural gas power plants using CFD and process co-simulation Department of Mechanical Engineering PhD Research Project Self Funded Prof M Pourkashanian
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include a combination of advanced unsteady computational fluid dynamics (CFD) and also the assessment of the design via real-time piloted simulations. The post is full time and is fixed term until 31
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include a combination of advanced unsteady computational fluid dynamics (CFD) and also the assessment of the design via real-time piloted simulations. The post is full time and is fixed term until 31
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in aerothermal experiments and/or turbine design is essential. Experience in data analysis, design using FEA and CAD packages, as well as CFD is also desirable. Good time management, organisation and
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in computational modelling and/or AI to apply. If you have worked with computational modelling using any of the following methods: finite volume/CFD, finite element/COMSOL Multiphysics, phase-field
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to assist multiscale modelling for zero-excess solid-state batteries. The candidate is expected to be experience in mesoscale modelling (finite element, CFD, phase-field theory) for addressing scientific
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. The successful applicant will engage in computational analyses, and experimental validation including CFD and FEA, to understand and predict the flow behaviour and interface bonding during injection over-moulding
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methods: finite volume/CFD, finite element/COMSOL Multiphysics, phase-field theory, lattice Boltzmann, then you will be suited for this project. Within the project, you will carry out meso-scale simulations
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achievements within turbomachinery, Computational Fluid Dynamics (CFD), aero-thermodynamics of power and propulsion systems, heat and mass transfer, thermo-fluid systems simulation and programming. You will have