73 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Argonne
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. The successful candidate will be a key contributor to a multidisciplinary co-design team spanning material science, computing, and electronic engineering, with the goal of enabling next-generation detector
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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 science
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The Applied Materials Division (AMD) at Argonne National Laboratory is looking to hire a Postdoctoral Appointee – Materials Science. The Applied Materials Division conducts applied research
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Knowledge of in RNA biology Experience with RNA CryoEM/crystallography/SAXS Prior experience with high-throughput or computational protein design/screening techniques Job Family Postdoctoral Job Profile
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The Decision and Infrastructure Sciences Division in Argonne’s Nuclear Technologies and National Security (NTNS) Directorate is seeking a highly qualified and motivated Postdoctoral Researcher
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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in atomic layer deposition of thin films, in situ metrology, interface science
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. Position Requirements Ph.D. completed in the past five years or soon-to-be completed in Chemical Engineering, Materials Science, Chemistry, Nuclear Engineering, or related field. Skill in devising and
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to internal and external researchers, enabling impactful experiments and analysis, advancing AI-ready data practices, and strengthening experimental–computational integration across the user program
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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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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