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element modeling, computational fluid dynamics). Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization. Experience in supply chains and hygrothermal
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capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas
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Computational Fluid Dynamics (CFD) and Conjugate Heat Transfer (CHT) modelling, which captures both the fluid & solid domains, as required to develop this understanding for engine-representative geometries and
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Physics , QCD , Quantum chaos and thermalization , Quantum Computation , Quantum Computing , Quantum Condensed Matter Theory , Quantum Control , Quantum Devices and Sensing , Quantum Dynamics , Quantum
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We are seeking an outstanding candidate for a PhD fellowship in the field of computational fluid and solid mechanics. The fellowship will start on September 1st, 2025, or as soon as possible after
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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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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
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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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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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics