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Université de Technologie de Belfort-Montbéliard | Belfort, Franche Comte | France | about 21 hours ago
for simulating such complex geometries. For example, the memory and computation time required become prohibitive with standard “black-box” finite element methods. The objective is therefore to develop a dedicated
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-time data acquisition during production, consulting, and prototype manufacturing. Graph neural networks provide an opportunity to operate on Mesh structured data utilized in Finite Element Method (FEM
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physical metallurgy experience or training in powder-based metal processing techniques, such as sintering and additive manufacturing first experience in computational modeling, including finite element
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mathematics with outstanding grades Excellent knowledge of continuum mechanics and finite element analysis Excellent coding skills Knowledge and experience with fracture and/or phase-field modeling and/or
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moving through different fluids. In this project, we are interested in developing moving mesh finite element methods for their dynamical simulation. We aim to produce efficient, accurate and robust
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and carry out finite element method (FEM) simulations. Our developments focus on higher efficiencies, more cost-effective manufacturing processes and materials, improved long-term stability and new
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and written. Solid skills in computer programming (Python / Matlab). Experience with CAD and CAE tools. Knowledge of computational fluid dynamics (CFD). Knowledge of finite element method (FEM
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assigned. Required Qualifications PhD in engineering, physics, mathematics or other related applied sciences. Five years of experience in theoretical and numerical evaluation of finite element methods
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of computational fluid dynamics (CFD). Knowledge of finite element method (FEM). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction
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are developing AI that can map welding processes in the automotive industry based on simulation data. We are looking for a student assistant with an interest in machine learning and finite element simulation. Your