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of the upgraded APS, leadership-class computing at the Argonne Leadership Computing Facility (ALCF), and state-of-the-art microscopy at the Center for Nanoscale Materials (CNM). Candidates with a strong background
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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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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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artificial intelligence/machine learning (AI/ML). The successful candidate will contribute to the group’s broad physics program, which includes precision Higgs and Standard Model measurements, and searches
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The Multiphysics Computations Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing high-fidelity scale-resolving computational fluid dynamics (CFD
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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measurements. Postdocs have an initial term of 1 year and can be renewed in 1 year increments; up to a total of 3 years depending on funding and performance. The expected starting date is Q3/Q4 of 2025
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-augmented AI tools Interfacing AI tools with experimental facilities at CNM and Argonne Key Responsibilities Research leadership (50%) Develop and lead an independent and collaborative research program in
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math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of