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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
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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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/reactions, with increasing emphasis on using artificial intelligence and quantum information science. The group has access to extensive laboratory and national computational resources and has significant
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effort at Argonne includes staff members from CPAC, the Computational Science division, and the HEP Detector group. It includes a vibrant community of postdoctoral researchers, graduate students, and
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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hardware trend. To help bridge the gap, the Argonne Leadership Computing Facility (ALCF) invites applications for a postdoctoral appointment on the subject of mixed/reduced precision computing on modern
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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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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-be completed (typically within the last 0-5 years ) Ph.D. in engineering, operations research, computer science, applied mathematics, or a related field. Demonstrated expertise in mathematical
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather