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This is an opportunity for a knowledgeable and creative individual to be part of a team using artificial intelligence and high-performance computing to evaluate the state of health (SOH
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of radiofrequency (MHz–GHz) nanoscale phenomena in systems relevant to microelectronics and quantum information science. Opportunities also exist for cross-platform studies integrating ultrafast TEM with ultrafast x
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, ptychography, Laue microdiffraction, or related coherent/imaging techniques. Proven ability to design, conduct, and analyze complex synchrotron experiments. Proficiency in scientific programming (Python, MATLAB
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy
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Extensive knowledge of Microsoft Excel and good computer programming skills Knowledge of techno-economic analysis and life cycle analysis Experience working with Argonne’s EverBatt model, GREET model, and
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limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory. The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division
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samples and characterize dynamic behaviors. The candidate will be part of a highly collaborative team and actively interact with other groups, including optics, computation, and time-resolved research
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Hands-on experience with two-dimensional materials modeling Proficiency in database development and management for computational materials data Strong programming skills and experience with software