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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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We are seeking a highly motivated Postdoctoral Researcher with expertise in computational biology, deep mutational scanning data, and generative artificial intelligence (AI). The successful
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, computational physics and x-ray science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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focus on our scientific program with CLAS12 (including the ALERT), Hall C and PRad-II at Jefferson Lab, and/or development of the EIC scientific program, including the development of a polarized light ion
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, large-scale computational science, and simulation of networked physical systems Familiarity with techniques for sensitivity analysis and handling high-dimensional problems Experience in power grid
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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In the Nanoscale Magnetic and Electronic Heterostructure Group of the Materials Science Division (MSD) we aim to understand the novel and emergent behavior in nanoscale magnetic and electronic
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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in experimental x-ray and materials science. Although exceptional candidates in
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(predoctoral) or PhD (postdoctoral) in Materials Science, Chemistry, Physics, or related area is required. Coursework in computer science or data science is desirable. Familiarity with research data management