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Field
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that integrate simulation, machine learning, and data analysis. Numerical optimization methods (e.g. machine learning including deep neural networks, reinforcement learning, data mining, genetic algorithms
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molecular dynamics simulations. This position emphasizes research in the modeling of complex chemical systems, where the candidate will integrate advanced simulation techniques with modern machine learning
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, collaboration, high-quality work, and real-world problem solving. This position will conduct numerical simulation studies, work on research projects with external partners, mentor and guide graduate student
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 6 hours ago
the commercialization of impactful energy technologies throughout the Department. OTC works closely with the Department’s numerous energy technology offices as well as a range of private organizations relevant
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innovative research focused on developing and modeling of multiphysics solutions to complex problems in porous materials. Candidates with a background in experimental and/or numerical multiphysics modeling
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of multiphysics solutions to complex problems in porous materials. Candidates with a background in experimental and/or numerical multiphysics modeling of porous media, applicable to both terrestrial and
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Neutrinos in the Multi-Messenger Era • Numerical Simulation of Core-collapse Supernovae IHEP values diversity and welcomes candidates from all backgrounds worldwide. Knowledge of the Chinese language is not
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: Expert on steels and steel welding or additive manufacturing Develop advanced machine learning framework to combine different modality and fields of data Conduct CALPHAD-based simulations in a high
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aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimising PIC algorithms for modern
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data