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theory, thermodynamics, statistical mechanics, or non-equilibrium physics Preferred Qualifications: Rich experience with transport measurements and characterization Basic knowledge of models of strongly
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technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes. The candidate will be a postdoctoral researcher within the Multiscale Materials (MsM) group of the Advanced
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capabilities in support of dramatic advances in our understanding of the physical world and using that knowledge to address the most pressing national and international concerns. It delivers leadership- class
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related field completed within the last 5 years Preferred Qualifications: Research experience or demonstrated knowledge in at least one of the following areas: Nanoscale optical spectroscopy, including
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or related Applied Economics discipline with a strong quantitative focus. Demonstrable knowledge of applied econometrics and statistical evaluation methods, such as: Difference-in-Differences (DiD
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in ORNL’s Center for Radiation Protection Knowledge (CRPK). The candidate will work with experts in computational radiation dosimetry and risk assessment. The candidate should be an independent thinker
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, a proven publication record, and effective interpersonal skills. Preferred Qualifications: Knowledge of graph neural networks and other geometric deep learning approaches for graph-structured
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knowledge of models of strongly correlated electron systems Proficiency with scripting or programmatic languages, such as Python, c, and matlab Excellent written and oral communication skills Motivated self
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of analytics into production systems Knowledge of experimental design, uncertainty quantification, scientific machine learning, or digital twin methodologies Experience collaborating across national laboratories
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. Experience with quantum algorithms (other than variational or adiabatic) and/or quantum hardware Knowledge of topological quantum field theories, topological band theory. Strong analytic mathematical skills