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LSST. Projects will draw on new and archival observations from optical ground-based (e.g., Zwicky Transient Facility) and satellite (e.g., TESS) observatories, with potential supplementary data from X
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LSST. Projects will draw on new and archival observations from optical ground-based (e.g., Zwicky Transient Facility) and satellite (e.g., TESS) observatories, with potential supplementary data from X
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: Bibliography and identification of the energy system components. Theoretical modeling and simulation of the flow systems. Data analysis. Assisting the PI and the sponsor in grant writing for other funding
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Responsibilities: The individual will be responsible for project execution and management. They will oversee data analysis, and present research findings in written reports and oral presentations to funding agency
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Qualifications: A PhD in Mechanical Engineering required; successful PhD thesis defense with pending graduation will be considered Experience with theoretical modelling and data analysis using Machine Learning is
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degree in transportation engineering. Demonstrated experience in transportation data analysis, network modeling, dynamic traffic assignment and simulation. Demonstrated experience in programming and