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the U.S. achieve energy goals. ESIA develops, deploy, and advances grid technologies that ensures a robust and secure U.S. grid transmission and distribution system. ESIA also collaborates with government
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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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models for microelectronics materials Curate, manage, and integrate heterogeneous datasets from experiments and simulations Collaborate closely with experimental teams to benchmark and refine computational
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samples and characterize dynamic behaviors. The candidate will be part of a highly collaborative team and actively interact with other groups, including optics, computation, and time-resolved research
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ability to work effectively across divisions, laboratories, universities, and industry Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications
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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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of organization. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires an on-site presence at the Argonne campus in Lemont, Illinois. Preferred
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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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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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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