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Field
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to open-source projects on model reduction, finite element methods, data assimilation and inverse modeling. You will collaborate with researchers by exchanging ideas and technical knowledge in computational
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to improve the accuracy of discontinuous Galerkin (DG) finite element methods. Recent work by our collaborator at the University of Tennessee has shown that optimal placement of high-order nodes can
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to improve the accuracy of discontinuous Galerkin (DG) finite element methods. Recent work by our collaborator at the University of Tennessee has shown that optimal placement of high-order nodes can
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models using experimental data for precise mapping of real processes Conducting detailed analyses of thermomechanical stresses in electrochemical converters using the finite element method (FEM
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engineering discipline Experience and skills · Proficiency with finite element modelling and FEA software like ABAQUS Explicit or LS-DYNA · Experience in impact modelling or continuum damage
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the following areas: - Structural engineering - Computational mechanics, including the Finite Element Method and structural dynamics Desirable qualifications In-depth knowledge in the following areas: - Have been
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. Extensive experience in the development and application of finite element method (FEM) or comparable methods for AM applications. Preferred Qualifications: Demonstrated expertise in multi-physics simulations
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the muscle architecture of the larva within the generative process. We recently extracted the muscles of the Drosophila larva body from a CT-scan recording. Furthermore, we developed a finite element
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measurements, and load measurements. Proficiency in computational methods, such as finite element analysis (FEA) and computational fluid dynamics (CFD). Experience with data acquisition and analysis using
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high computational cost presents a challenge for real-time process control. This project aims to overcome this limitation by integrating real-world casting data, process parameters, and finite element