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Expertise in numerical methods (finite element, finite differences, finite volumes) Expertise in programming (Python, Fortran, R, Matlab) Expertise in geogrpahic infomation systems (QGIS) Expertise in LaTeX
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a journal publication on the findings. The work will involve physics-based finite element simulations of metamaterial structures, work on analysis methods to understand relations between structure and
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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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change (8 points). Proven knowledge and experience in numerical simulation in industrial processes, specifically in additive manufacturing or LAM-DED, including the use of tools such as the Finite Element
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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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, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data-driven techniques. The Vienna School of Mathematics doctoral program offers excellent conditions for
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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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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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element simulations and similar scientific calculation tools and programs Willingness to explore and develop new scientific methods Enthusiasm for new technical solutions including machine learning
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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