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. Experience with numerical methods, finite element method, statistics and machine learning is desirable. How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement
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loading conditions. By generating datasets from finite element simulations, ML models can learn the mapping between unit cell design parameters and homogenised properties. State-of-the-art approaches
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experience in a range of industrially relevant computational engineering techniques. You will develop expertise in high-order finite element methods, mesh adaptation techniques, advanced parallel programming
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Mathematics, Applied Mechanics, or related disciplines (a minimum honours degree at UK first or upper second-class level) Experience in computational fluid dynamic/finite element modelling by using commercial
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meeting these needs, this PhD project will involve the research and development of new computational technologies, based on the boundary element and finite element methods, in a high-performance computing
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validation experiments for modelling • Computational fluid dynamics techniques • Finite element analysis method • Reviewing literature, planning and managing research, writing technical report / paper
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computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the research will be the inclusion stochastic elements
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skills include: Interest or background in composite materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a
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distribution in wire based additive manufacturing • Calibration and validation experiments for modelling • Temperature monitoring techniques • Finite element analysis method • Reviewing literature, planning and
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simulations and finite element analysis, with high-heat flux electron beam experiments. The research will simulate and replicate steady, cyclic, and transient thermal loads to better understand PFM behaviour