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A postdoctoral position on exascale atomistic simulations, AI/machine learning and data analysis of ferroelectric devices is available immediately at the Center for Nanoscale Materials (CNM
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-CCE Scaling Machine Learning. The HEP Division performs cutting-edge research facilitated through advanced detector development, high-performance supercomputing (HPC), and innovative electronic and
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multidisciplinary team comprised of fellow postdoctoral appointees, experimentalists, and staff scientists, with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with
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models for turbulent reacting flows. Development and application of machine learning tools in one or more of these areas: chemical kinetics, turbulent combustion, and extreme event prediction. Job Family
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above Experience with machine learning methods and deep learning frameworks such as PyTorch Knowledge of software development practices and techniques for computational and data-intensive science problems
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Argonne National Laboratory invites applications from outstanding candidates with a background in artificial intelligence (AI) and machine learning (ML) for postdoctoral research positions in
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knowledge of advances in modeling, simulation, machine learning, and data analysis. Employment of these models on high performance computers and cloud-based infrastructures. Design, develop, and deploy novel