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machine learning models at a world-class high-performance computing facility The candidate will have access to state-of-the-art computing resources, including: NVIDIA DGX-2 Systems: Powerful platforms
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-of-the-art facilities and resources at the APS and across Argonne. Competitive compensation and benefits; professional development and conference travel support. Initial appointment for two years, with
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critical material technologies and meeting society’s growing needs for water and energy resources. The Applied Materials Division focuses on bridging the gap between research and real-world applications. By
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resources—including the Autonomous Sputter Beam Epitaxy system, the QuEEN-M electron microscopy platform, and synchrotron X-ray beamlines at the Advanced Photon Source. This is an outstanding opportunity
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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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math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of
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facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and
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critical material technologies and meeting society’s growing needs for water and energy resources. The Applied Materials Division focuses on bridging the gap between research and real-world applications. By
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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candidate will conduct research related to a wide range of topic areas including the analysis of energy and power systems, optimization of veriable energy resources, electricity market design and operation