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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates
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plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
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competitive residency program with 25 positions, we offer 9 fellowships and participate in numerous graduate school and the MD/PhD program of the CU School of Medicine. Why work for the University? We have
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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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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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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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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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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