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This is an opportunity for a knowledgeable and creative individual to be part of a team developing statistical methods for model selection, parameter inference, and uncertainty quantification and
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mechanics models and statistical reliability models (e.g. Weibull failure models). Materials of interest include high-temperature alloys, ceramics, and ceramic matrix composites. The goal is to enhance
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. Contribute to ongoing development and analysis using GCMat, an existing agent-based model of critical material supply chains. Use advanced statistical analysis to estimate mine development costs and associated
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, statistical analysis, and predictive modeling Familiarity with economics as it applies to mining, energy industries, and manufacturing Familiarity with resource extraction and processing practices Experience
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engineering package (e.g. pandas). Solid foundation in mathematics/statistics with experience in cyber-physical systems modeling and analysis. Ability to work both independently and collaboratively in a team
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, applied economics. Experience in statistics and statistical analysis. Experience with environmental systems is preferred but not required. Experience working with federal agencies is preferred but not
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integrated assessment models. In several instances, engineering and/or statistical models would need to be developed to characterize input datasets for energy use, emissions, performance, and cost attributes
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) on HPC systems Skilled in data analysis, statistics, and visualization, especially on large datasets. Knowledge of developing flood observation training datasets from multiple sources. Experience in
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literature and statistics from US Department of Agriculture and other agencies. The candidate will work on projects to evaluate the synergies between the decarbonization of U.S. agriculture and the production
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analysis, statistics, and visualization, especially on large datasets. Experience in writing and modifying scientific code in Fortran, C, C++, CUDA and Python. Effective written and oral communication skills