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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, industrial engineering, electrical engineering, environmental
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/ML techniques for real-time, real-world data Transport and dispersion modeling Fate modeling of materials in the atmosphere Applied statistics Data analytics Deliver ORNL’s mission by aligning
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manufacturing competitiveness analysis relevant to advanced manufacturing technologies. The team builds and applies analysis tools and analytics to draw insights on the manufacturing sector’s impact on energy
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data analytics using tools in programming languages such as Python, PyTorch, Pandas, Scikit Learn, etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient
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critical to understanding target behavior during irradiation in the High Flux Isotope Reactor (HFIR). This could also involve development, validation, and deployment of new physical and analytical testing