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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
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. As part of this PhD, the candidate will: Conduct an integrative review of established competency models Create assessment tools (which may include use of AI tools) to measure CLMA proficiency
Searches related to modeling and simulation
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