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for quantum information science, but many open questions remain regarding how to control the morphology and crystallinity of these host materials for exemplary performace as hosts for optically addressable spin
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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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, project presentations, and other regular channels. Position Requirements This level of knowledge is typically achieved through a formal education in chemical engineering, mechanical engineering, or a
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, project presentations, and other regular channels. Position Requirements Skill in modeling, processing, and analyzing computational results to inform accompanying experimental efforts. Skill in the use
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manuscript to be submitted). Position Requirements This level of knowledge is typically achieved through a formal education in electrical engineering, mechanical engineering, physics, or a related field at the
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: 10.1038/s41467-023-39984-3 Position Requirements This level of knowledge is typically achieved through a formal education in Physics, or a related field at the PhD level with zero to five years
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, networking, and leadership. Position Requirements Required Knowledge, Skills, and Experience: This level of knowledge is typically achieved through a formal education in economics, operations research, public
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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
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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