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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python
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on experiment progress, technique development, and new initiatives to peer reviewers and Q-NEXT program managers Position Requirements Completed Ph.D. within the last 0-5 years (or soon-to-be-completed) in
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The Chemical and Fuel Cycle Technologies division is seeking Postdoctoral Appointees to join a multidisciplinary team developing molten salt-based chemical and electrochemical processes geared
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We are seeking a highly motivated and adaptable postdoctoral researcher to join the Laboratory Directed Research and Development (LDRD) project FREEZE (Fundamental Research on Energy-Efficient Zonal
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diamond membranes, defect synthesis, quantum experiment development, and optical spectroscopy. The successful candidate will join a dynamic, collaborative team working across the Argonne community and with
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, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI
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The Materials Science Division (MSD) at Argonne National Laboratory is seeking highly motivated applicants for a postdoctoral appointee to join a multidisciplinary team developing next-generation
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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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-ion battery materials. The focus is to develop atomic layer processing methods to tailor the surface properties of lithium ion battery electrodes using nanoscale thin films and surface treatments
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research to develop sustainable innovative technologies to improve the efficiency of resource and energy utilization; to increase our economic competitiveness; and to enhance our national security