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discovering research and potentially pursuing a PhD. Expected skills • Solid background in numerical methods (PDEs, finite elements, scientific computing). • Interest in modeling, model order reduction, and
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) transport; • Are familiar with chemical simulation techniques, including but not limited to density functional theory, molecular dynamics, (kinetic) Monte Carlo modeling, finite-element modeling, and multi
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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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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 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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Strong background in computational science, applied mathematics, or computational biology Ideally, familiarity with numerical methods for PDEs (e.g., finite difference, finite element) HPC experience is a
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or morphodynamic applications in estuarine and coastal environments.. Proven experience in scientific programming of numerical methods (the finite element method in particular) is a strong asset. Please submit any
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communication skills in English Strong background and knowledge of the Finite Element Method or any other relevant numerical methodology. Other valued skills (not mandatory): Authorship or co-authorship of journal
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analytical skills are desirable as well as some programming experience, while initial exposure to Finite Element Methods & object-oriented C++ programming language would be a plus, but is not required. We also
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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