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in Discontinuous Galerkin Finite Element Methods and the Julia programming language will admitted to the selection. Workplan and the objectives to achieve: This scholarship aims to advance a time
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Engineering Master Degree in Earth Sciences Experience in programming and high-performance computing (HPC). Experience in finite element numerical modelling and stabilisation techniques. Experience in
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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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knowledge of numerical methods - knowledge of free-surface flows, granular flows - proven experience in numerical simulation (finite elements, finite volumes, CFD, LES, etc.) - proficiency in basic scientific
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 2 months ago
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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of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux operating systems
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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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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fields, and risk damaging the part during fabrication. Finite element analysis (FEA) models, while capable of delivering detailed spatiotemporal distributions of thermal variables, suffer from limited
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using language identification, such as text corpora for rare languages. Language identification methods ground their predictions on training corpora for a finite number of separate languages. In practice