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Field
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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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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
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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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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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engineering Substantial experience in programming in C++ Substantial knowledge about Finite Element Method (FEM), Smoothed Particle Hydrodynamics (SPH), and/or peridynamics Solid knowledge in computational
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, mechanical CAD, PCB design tools, and finite element electromagnetic analysis software. Experience creating engineering documents, reports, and technical publications, including drawings, procedures, and
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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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signal analysis Computational acoustics methods such as finite element, boundary element analysis or other computational methods development Flow excitation mechanisms such as gust response and turbulent
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techniques and associated tools (examples include, but are not limited to machine learning, density-functional-theory, materials informatics, finite-element modelling, phase-field modelling), and demonstrated
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of materials mechanics, e.g., plasticity, porous plasticity, crystal plasticity and damage mechanics. Knowledge of micromechanical modelling. Knowledge of non-linear finite element methods. Knowledge of FFT