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The Laboratory for Applied mathematics, Numerical software, and Statistics (LANS) and the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invite applicants for a
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with ANL staff to review, validate, and extend methods for predicting the reliability of high temperature structural components. Relevant methods include deterministic and statistic continuum damage
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and hydrological models, numerical modeling, data sets, and data analysis. Knowledge of atmospheric observational datasets, data assimilation techniques and statistics. Experience using HPC systems
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data sets and developing and using statistical tools, e.g., Python, R. Skills in working in a multidisciplinary team environment. Skills in oral and written communication. Understanding of basic