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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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. Preferred Knowledge, Skills, and Experience Prior experience with high-throughput or computational protein design/screening techniques. Background in structural biology (CryoEM/crystallography) Knowledge
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good
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to the development of new research directions aligned with program goals. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Chemical Engineering, Materials
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, instrumentation, modeling, and data science Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field(s) of materials science, physics, computational science, or a related field
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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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Argonne National Laboratory invites applications for postdoctoral research positions in experimental physics, with a focus on advancing superconducting particle detector technology for next
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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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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 Argonne Leadership Computing Facility (ALCF) is dedicated to advancing scientific discoveries and engineering breakthroughs by providing world-class computing facilities in collaboration with