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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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/modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a closely related field
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knowledge in using HPC systems for visualization and analysis Technical knowledge of large, dynamical systems (preferably the atmosphere) Knowledge and experience in writing scientific code Skills in clear
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs
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MEP Group Argonne National Laboratory, situated near Chicago, is a prominent multidisciplinary science and engineering research center. The Medium Energy Group in the Physics Division, comprises eight
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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
5 years or soon-to-be-completed in physics, materials science, chemistry, chemical engineering, or a related field. Demonstrated expertise in synchrotron-based XFM or related X-ray microscopy methods
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domains such as nontrivial skyrmions, using external stimuli (e.g., optical excitations, electric and magnetic fields) and internal nanoscale heterogeneity, defects, and interfaces (e.g., twisting