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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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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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. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence. The project involves: 1
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The Cosmological Physics and Advanced Computing (CPAC) group at Argonne National Laboratory invites applications for a postdoctoral researcher to work closely with Dr. Lindsey Bleem
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Extensive knowledge of Microsoft Excel and good computer programming skills Knowledge of techno-economic analysis and life cycle analysis Experience working with Argonne’s EverBatt model, GREET model, and
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limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory. The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division
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and program managers. Position Requirements Minimum Education / Experience Requirements: A Ph.D. in physics, applied physics, electrical engineering, or related field. Additional Requirements: Normal
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy
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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