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-edge projects aimed at improving sustainable transportation networks using advanced computational techniques, data analysis, and artificial intelligence. We seek candidates specializing in the following
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to perform RFID testing and analysis. The student is expected to conduct research and testing for the lab’s projects pertaining to LANL, which includes both running tests and processing the data gathered
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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implementation. The position emphasizes community-based fieldwork, qualitative interviewing, focus groups, and comparative case study analysis, with three focal communities who have already expressed support for
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to perform RFID testing and analysis. The student is expected to conduct research and testing for the lab’s projects pertaining to LANL, which includes both running tests and processing the data gathered