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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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workflows for descriptor based microstructure reconstruction to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property
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reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be complemented by own lab testing e.g., SSRT incl
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materials (including, magnetic, ferroelectric, 2D and correlated materials) and leverage their complex physics to design and simulate advanced nanoelectronic devices. These devices will replicate the finer
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simulation with flotation Presentation of own results at international conferences, in peer-reviewed journal publications and in a PhD thesis Cosupervision of related MSc topics and cooperation with other
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CMOS components. Ideally, you have already gained experience in using circuit simulation and 3D field simulation programs, for example, Cadence Virtuoso, Advanced Design System (ADS), the CST Studio
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://github.com/FZJ-IEK3-VSA/RESKit ). This framework currently uses historical weather data to model energy output and will be further developed to allow the simulation of renewable electricity production under
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of Parasitism”, which includes a variety of theoretical, simulation, and experimental projects from different disciplines. The key goals of the project are to elucidate physical mechanisms that govern trypanosome
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during downstream processing. Theoretical investigation of molecule stability during DSP, using molecular interaction simulations such as e.g. Molecular dynamics (MD). Combination of PAT and data driven
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Some experience with numerical simulations such as the Finite Element Method (FEM) and Multi-Body Simulation (MBS) is a plus. We offer: a fascinating understanding at mobility in general with a