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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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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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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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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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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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Argonne National Laboratory, a U.S. Department of Energy multidisciplinary science and engineering research center, is committed to finding solutions for national priorities, including advancing
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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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, 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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(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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field. Solid knowledge, and independent research capability in optimization, computing, power system engineering with track records of publications. Proficient in implementing control and optimization