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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Laboratory’s High Energy Physics (HEP) Division
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The Data Science and Learning Division (DSL) of the Computing, Environment and Life Sciences Directorate (CELS) and the Materials Science Division (MSD) of the Physical Sciences and Engineering
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Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML) for applications in
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This position focuses on the research and development of novel radiation detectors and associated edge-computing circuits and algorithms for X-ray, particle, and nuclear physics experiments
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Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling. Density Functional Theory (DFT) for surfaces and
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow
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Argonne National Laboratory invites applications for postdoctoral research positions in experimental physics, with a focus on advancing superconducting particle detector technology for next
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus