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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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. This is an exciting opportunity to work within a collaborative group with deep expertise in silicon detectors, Trigger/DAQ (TDAQ) systems, software, and computing. The Argonne ATLAS group plays 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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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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closing this gap. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary
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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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nitrogen-vacancy (NV) diamond quantum magnetometry for high-energy physics experiments. The HEP Division performs cutting-edge research leveraging advanced detector development, high-performance computing
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with potential impact across quantum networking, communications, and computing. Research Focus Design and fabricate superconducting devices that leverage the nonlinear kinetic inductance of thin
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research outcomes through publications, presentations, software, datasets, and internal reports Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in chemistry, chemical