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machine learning methods. Provide theoretical predictions to guide experiments, and atomic-scale physical understanding to experimental observations. Publishing findings in peer-reviewed journals
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interactions. Analyze data to advance fundamental understanding of wall-bounded turbulence and inform predictive modeling. 20% - Collaboration & Mentorship Work closely with PI, graduate, and undergraduate
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, roughness, and porous-media interactions. Analyze data to advance fundamental understanding of wall-bounded turbulence and inform predictive modeling. 20% - Collaboration & Mentorship Work closely with PI
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