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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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The Argonne National Laboratory at U.S. Department of Energy supported research programs invites applications for a Postdoctoral Research Associate position focused on understanding the relative
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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well as in industry and at other national laboratories. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years)in Engineering or similar program. At least 2
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symmetries, and nuclear data. LER also plays a critical role for the ATLAS National User Facility, where it provides support for ATLAS Users, conducts its own research program, and develops and operates
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and machine learning techniques in analyzing supply chain risk. Ability to develop and synthesize visualizations to effectively communicate analysis results. Strong programming skills in statistical
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The Group Leader (GL) for the Electron and X-ray Microscopy (EXM) Group at the Center for Nanoscale Materials (CNM) develops, leads, and executes world-class R&D programs in electron and X-ray
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2.0) program. The collaboration team includes Clarence Chang, Tim Hobbs, Dafei Jin, Yi Li, Marharyta Lisovenko, Valentine Novosad, Zain Saleem, Tanner Trickle, and Gensheng Wang. We seek highly
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an independently-funded research program within 2-3 years. The successful candidate will develop and apply advanced data-driven methodologies to accelerate discovery in materials/chemistry design, characterization
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environment. Demonstrated strong analytical and problem-solving skills. Experience in studying geological or biological systems, and tomography are beneficial. Programming expertise in Python or other