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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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Knowledge of Matlab, and web-based technologies is of advantage Knowledge in using high-performance compute architectures Experience in implementing and optimizing scientific numeric analysis methods and
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these nanocomposites, we are looking for a postdoc to further develop high performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core
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, engineering, materials science, maths, or computer science), or equivalent experience Experience with uncertainty quantification or error analysis Familiarity with numerical methods (e.g., Monte Carlo, Finite
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tools in combustion. Our computational codes are also used by various international research institutions. Both experimental and numerical projects are conducted in parallel providing a platform for
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Strong foundation in CFD, Programming proficiency such as Python, AI/ML techniques, Experience with parallel computing on CPU/GPU cluster, use of CUDA, MPI is a plus. Experience Experience with open-source
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skills and experience with numerical modeling and particle-based methods Interest in working closely with experimentalists Excellent written and spoken English skills Experience with parallel programming
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. Strong background in numerical linear algebra, algorithm design, and parallel computing. Proficiency in programming languages such as python. Experience with HPC environments and linear algebra
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between the Universities of Cambridge and Bonn and numerous international partners, and funded by Stiftung Mercator. The programme investigates how to place the questions of social justice and environmental