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for validation of CFD results. Implement novel unsteady CFD and next generation in-house AI based design tools validated by the gathered experimental data on GKN resources with tight collaboration
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments and real-life monitoring to support our findings. Besides research, our division is actively involved in
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environments ensure safe operations Our activities are primarily related to the development and application of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments
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of sustainable power production and propulsion systems through your expertise in Computational Fluid Dynamics (CFD). Detailed description of work duties Developing Advanced CFD Models: You will be primarily
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, for example a 4-year bachelor's degree is accepted. Strong written and verbal communication skills in English Meritorious qualifications Powertrain mechanics, tribology Modelling (FEM, CFD) Materials
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reacting flows. A novel aspect of the project is the use of highly perturbed laminar flame simulations to inform CFD modelling of turbulent combustion in lean hydrogen-air mixtures. Experimental work will be