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The position is part of a new collaboration between Argonne National Laboratory, the University of Notre Dame, and UIUC, supported by the Quantum Information Science Enabled Discovery 2.0 (QuantISED
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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
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data processing and interpretation workflows. The appointee will also pursue a collaborative science program leveraging the developing instrument capabilities, leading to peer-reviewed publications 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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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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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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field. Solid knowledge, and independent research capability in optimization, computing, power system engineering with track records of publications. Proficient in implementing control and optimization
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. The cosmology effort at Argonne includes staff members from the CPAC group, the Computational Science division, and the HEP Detector Group. The group also includes many postdocs, and a number of graduate and
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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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services for leadership computing facilities Strengthen ALCF’s role in shaping human-centered AI systems for science, bridging visualization, AI, and HPC Contribute to DOE-wide efforts in AI-ready workflows