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approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim
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data from the European XFEL facility at DESY. Project website: https://www.mpinat.mpg.de/628848/SM-Ultrafast-XRay-Diffraction Your profile Eligible candidates have strong skills in computational physics
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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degree in physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the above mentioned fields. What we offer State of the art on-site high performance/GPU
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optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms Publish and present your results in peer-reviewed journals and at
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at the Technical University of Munich (TUM) invites applications for one PhD position. The student will work on developing scalable distributed preconditioners in Ginkgo (https://github.com/ginkgo-project/ginkgo