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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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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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finite elements) as well as alternative discretization methods (e.g., Lattice Boltzmann Methods), and high-performance computing. A selection of possible research areas can be found on our website: https
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science, physics, computational science or similar, with experience in modeling and simulation Strong understanding of the (computational) mechanics of solids and the finite element method and/or spectral
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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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, 2025. We are looking for: The applicant should perform active research in numerical analysis of finite element or finite volume methods for coupled problems in one of the application areas of the group
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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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characterization of interface deformation mechanisms, including advanced SEM and TEM methods Finite Element Modeling to design and optimize micromechanical testing geometries Timely dissemination of research
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formation of polyhalogens. The applied methods will include first principles methods like DFT, both for finite and periodic systems, ab initio molecular dynamics simulations and calculations of various
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properties (k, cp) as f(T) Particle Finite Element Method (PFEM) simulations Co-ordination of collaboration with project partners Evaluation, compilation and presentation of results, documentation, preparation