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, computational physics and x-ray science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris
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prototype, benchmark, and evaluate strategies to better support these workloads for Aurora. Position Requirements Required skills and qualifications: A recent PhD (within 5 years) in computer science
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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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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(predoctoral) or PhD (postdoctoral) in Materials Science, Chemistry, Physics, or related area is required. Coursework in computer science or data science is desirable. Familiarity with research data management
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policy, environmental science, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven
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years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field. Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding
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The Applied Materials Division, Process R&D and Scale up Group is seeking a postdoctoral candidate to conduct general research in material science and electrochemistry related to next generation
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of impact, safety, respect, integrity, and teamwork. This level of knowledge is typically achieved through a formal education in materials science, physics or related discipline at the PhD level or