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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, large-scale computational science, and simulation of networked physical systems Familiarity with techniques for sensitivity analysis and handling high-dimensional problems Experience in power grid
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, the ALCF is studying the application of these techniques to a variety of our science applications, including but not limited to: Computational Chemistry, Plasma Physics, High Energy Physics, analysis
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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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your PhD in computer science or engineering, the physical sciences, or a related field within the last five years. Comprehensive programming proficiency, preferably in Python. Experience with machine
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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are seeking an postdoctoral appointee to contribute to this research to understand the underlying physics of spin and charge based memory materials using advanced in-situ transmission electron microscopy (TEM
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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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the domains of environmental, water, and energy system analysis. Prepares reports, papers, and presentations for conferences, workshops, and technical journals. Supports program development including
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, in Electrical Engineering and Computer Science or related field obtained within the last five years. Experience with X-ray physics or optical wave modeling. Proficiency in programming with Python
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Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead efforts to discover and design quantum emitters with desirable properties for quantum information science (QIS