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Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
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characterization techniques with mechanical behavior and finite element methods. The postdoctoral candidate will develop the processes needed to connect mechanical testing data with 3D microstructure of nuclear
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safety at ORNL and DOE sites. This position resides in the Performance Engineering group in the Data and AI Systems Section in Computer Science and Mathematics division within Computing and Computational
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Sciences Division (CSD), Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL). The postdoc will perform molecular dynamics simulations, statistical mechanics (e.g., rate theory) and
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across the laboratory. Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Postdocs: Applicants
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spectroscopies, or nanophotonics Basic understanding of data analytics techniques. Preferred Qualifications: Experience with spin-based or squeezed quantum sensors. Experience with dilution refrigeration
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(LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment. Postdocs: Applicants cannot
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fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Postdocs: Applicants cannot have received their Ph.D. more than five years