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of flow behaviours. This challenges the design and substantiation of such systems. A new and versatile experimental facility has been developed by the Thermo-Fluids group at the University of Manchester
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project aims at improving existing methods and exploring new ways to efficiently and systematically model and simulate all aspects of CVD processes. The basis for this will be Computational Fluid Dynamics
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development of special phase field and phase field crystal models coupling newly developed approaches with established approaches for simulating e.g. mechanical properties and the flow of fluids implementation
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that can flow without resistance, mimicking the behaviour of quantum fluids. These systems, known as quantum fluids of light, promise revolutionary applications in low-energy photonic devices, including
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This is a self-funded opportunity relying on Computational Fluid Dynamics (CFD) and wind tunnel testing to further the design of porous airfoils with superior aerodynamic efficiency. Building
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systems, enabling global scalability and accessibility. Using advanced computational fluid dynamics (CFD) approaches, the project is aimed at advancing modelling capabilities for the prediction of energy
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(for plasma catalysis). Computational fluid dynamics & kinetic modelling of plasma reactor design. You will publish scientific articles related to the research project. You will carry out a limited number of
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from