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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow
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science, engineering, computational science, a physical science (materials science, chemistry, physics etc.), or related field. Hands-on experience with AI frameworks and employing large language models. Strong Python
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer
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, from nuclear physics and materials science to biology and advanced computer science. The Physics Division (PHY) at Argonne has a long and distinguished history in nuclear physics and currently has a
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limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory. The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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The Center for Nanoscale Materials (CNM) and the Materials Science Division (MSD) at Argonne National Laboratory are jointly seeking a highly motivated postdoctoral researcher to advance quantum