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Field
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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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-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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Method (FEM) (8 points). Educational background and proven experience in modelling mathematical programming problems using programming languages such as Python, C, Fortran, etc. (8 points). Proven
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familiarity with RF design, synthesis, FEM, and MoM simulations. Quick learning skills with the ability to grasp new concepts from literature are highly appreciated. Problem-Solving: You demonstrate a
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participation in meetings and workshops. Your daily tasks will include coding scripts and performing computations using CFD, FEM, and acoustics software. Over the course of the position, you will gradually
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using CFD, FEM, and acoustics software. Over the course of the position, you will gradually develop skills in writing technical reports and in publishing high-quality scientific papers in journals and
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related field * ability to work in a team in the field of scientific research * documented scientific achievements (at least 3 publications indexed in Web of Science) * knowledge of FEM software and
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modeling (FEM), and thermodynamic/kinetic simulations using tools such as Thermo-Calc and CALPHAD first experience in applying artificial intelligence and machine learning techniques to Materials Science
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comparable field (bachelor's/master's degree) Interest in modern manufacturing technologies and welding processes Experience with Python/data analysis/FEM Structured, independent working style and ability
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shaping the change! We support you in your work with: A research topic with strong relevance for future memory technologies Work with a well-established FEM simulation tool Close supervision and integration