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                ) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s 
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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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                information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum 
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                We seek a postdoctoral scientist with expertise in electrodeposition science and technology. Exposure to microelectronics applications is desirable, as is familiarity with progamming and interfacing 
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                , 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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                ). 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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                in the past 5 years or soon-to-be completed in Geoscience, Physics, Chemistry, Materials/Mechanical/Chemical Engineering, or a related field. Experience and knowledge in one or more of the following 
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                The Chemical Sciences and Engineering Division is seeking a highly qualified and motivated postdoctoral researcher to join our team in the area of light-matter interactions, with a particular focus 
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                Argonne’s Nanoscience and Technology Division seeks a postdoctoral scientist to advance transmission electron microscopy (TEM) studies of materials and interfaces relevant to microelectronics 
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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