90 information-security "https:" "https:" "UCL" "UCL" Postdoctoral research jobs at Argonne
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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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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks an outstanding postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials
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optimization technologies are revolutionizing the way power grid is operated and planned. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using
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employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative
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benefits! As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and
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measurement Experience in x-ray diffraction techniques Experience designing and building experimental control and data acquisition systems Ability to model Argonne’s core values of impact, safety, respect
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employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace
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techniques (e.g., BCDI, ptychography, XPCS) and associated data analysis. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Interpersonal skills, oral and written
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benefits! As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and
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on the development of the SPHEREx Legacy Galaxy Clusters Catalog. The successful candidate will lead analyses to characterize galaxy populations in clusters using SPHEREx data in combination with complementary wide