82 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Argonne
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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne
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multidisciplinary team, the candidate will work at the intersection of AI/ML, domain sciences, and high-performance computing. The role requires a strong foundation in LLMs and machine learning, along with
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Argonne National Laboratory invites applications for a postdoctoral research position in experimental physics, with a focus on advancing superconducting particle detector technology for next
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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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The Materials Science Division (MSD) at Argonne National Laboratory is seeking a postdoctoral appointee to join the Nanoscale Magnetic and Electronic Heterostructures group. This position will focus
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees
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capable of hypothesis generation, experimental design, data analysis, and iterative learning in biological contexts. This project seeks to transform how computational and experimental biology research is
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) in the field of accelerator physics or a closely related science and engineering discipline Strong experience developing and applying computational modeling and simulation Familiarity with accelerator
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The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
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looking for candidates whose research program aligns with the 2023 Long Range Plan for Nuclear Physics, focusing on lab-based tests of fundamental symmetries via precision experiments. The ideal candidate