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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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: Completed doctoral or PhD studies in technical sciences Excellent knowledge in the field of computational mechanics and experience in the development of corresponding finite element codes, including
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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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carbon emissions. The EcoTray project aims to develop a validated, high-resolution finite element simulation framework that integrates experimentally calibrated material models and tribological behavior
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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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engineering, physics or similar (at least master’s level) Expertise in Python programming Expertise in design and evaluation of electrical machines and magnetic circuit Fundamental knowledge in Matlab, finite
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engineering content (e.g. e.g. civil engineering; structural engineering; finite element modelling) across all years of our undergraduate and postgraduate Construction, Engineering and Environment programmes
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with benefits. Qualifications 3 or more years Mechanical design experience focused on cost and manufacturability (Required) Experience in finite element analysis and mechanical simulation (Required
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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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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