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on practical AI systems that connect research prototypes to real-world deployment environments, including cloud, secure enclaves, trusted research environments, and leadership computing platforms
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winds, land–atmosphere interactions, or aerosol–cloud interactions Strong experience in numerical modeling and high-performance computing • Experience applying AI/ML methods to model development, with
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excited to contribute to both the scientific and technical aspects of the ATLAS program in a highly collaborative research environment. Position Requirements Recent or soon-to-be-completed PhD (within the
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the research sponsor(s). Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical, aerospace, energy engineering or a closely related
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studies of a LPA-based FEL facility, and writing up research findings for peer-reviewed publication. Position Requirements PhD in accelerator physics or closely related field within the past 0-5 years
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is extended yearly. Position Requirements A recent PhD (within 5 years) in computational chemistry, chemistry, materials science, physics, computational science, computer science, engineering, or a
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usefulness for accelerator operation. Position Requirements PhD completed in the past 5 years or soon-to-be completed in accelerator physics or a related field is strongly preferred. PhD graduates in other
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. Position Requirements PhD completed within the last 5 years, or expected soon, in accelerator physics or a closely related field. Candidates with PhDs in physics, applied mathematics, computational science
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other large-team scientific projects in artificial intelligence, materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Recently completed PhD within the last
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interested in pushing the boundary of predictability. Position Requirements Recent or soon-to-be-completed PhD (completed within the last 0-5 years) in geophysical sciences, computer science, or machine