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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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We are seeking a highly motivated and creative Postdoctoral Researcher to join the X-ray Science Division (XSD) at Argonne National Laboratory. The successful candidate will develop web-based AI
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The Applied Materials Division (AMD) at Argonne National Laboratory is looking to hire a Postdoctoral Appointee – Materials Science. The Applied Materials Division conducts applied research
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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growth, electricity usage, and their implications for U.S. supply chains and energy infrastructure plans. The successful candidate will apply methods from economics, supply chain risk analysis, and data
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Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Chemistry, Chemical Engineering, Mechanical Engineering, Materials Science, Electrochemistry, or a related
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regulations and contract. Skill in modeling, processing, and analyzing computational results to inform accompanying experimental efforts. Skill in the use of modern collaborative coding practices Demonstrated
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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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The Energy Systems and Infrastructure Assessment (ESIA) division provides the rationale for decision makers to improve energy efficiency. We develop and use analytic tools to help the U.S. achieve
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, asphaltenes, resins, and kerogen molecules and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will