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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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years) in Chemical Engineering, Environmental engineering, Bioengineering, or a closely related field, with 0 to 5 years of experience, or the equivalent experience through practical application in a
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ceramic engineering including hands-on, practical laboratory experience with material synthesis and processing, and analytical methods. Hands-on experience: XRD & Refinement, SEM-EDX, TGA-MS, DSC, BET, coin
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Recent or soon-to-be-completed Ph.D. in Physics, Materials Science, Electrical Engineering, or a related field Hands-on experience in epitaxial thin-film growth and characterization (oxides preferred
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the last 0-5 years) in geology, earth sciences, chemistry, chemical engineering, or materials engineering (those with other degrees but have similar skills to those listed will be considered). Experience in
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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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). About Argonne and the Physics Division: Argonne is a multidisciplinary science and engineering research center, where talented scientists and engineers work together to answer the biggest questions facing
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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