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(mechanical, electromagnetic, and, possibly, fluid-dynamic) and multi-scale simulations for drone components using finite element tools (e.g., Abaqus, Comsol). · Supporting the development of an AI
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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expertise and supervision of experienced researchers from multiple institutes at Forschungszentrum Jülich. As one of Europe’s largest and most multidisciplinary research centers, Forschungszentrum Jülich
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Description The Research Training Group (in German: Graduiertenkolleg, GRK) RTG2670 “Beyond Amphiphilicity: Self-Organization of Soft Matter Via Multiple Noncovalent Interactions” in the second
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expertise and supervision of experienced researchers from multiple institutes at Forschungszentrum Jülich. As one of Europe’s largest and most multidisciplinary research centers, Forschungszentrum Jülich
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environments. The network emphasizes innovation through the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with
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algorithms for application parallelization, simulators and virtual platforms for application- and architecture exploration, hardware/software co-design and operating/runtime systems. Typical application
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expertise and supervision of experienced researchers from multiple institutes at Forschungszentrum Jülich. As one of Europe’s largest and most multidisciplinary research centers, Forschungszentrum Jülich
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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in our laboratory (see Nielsen et al. 2024, Nature). We also strive for implementing nano discs from polymers or MSPs to extract or stabilize hDAT. The main task is to solve multiple structures of hDAT