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interact, with applications in sustainable mobility, electrification, resilience, equity and policy analysis. The successful candidate will be expected to contribute intellectually to the theoretical
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, tracking, spatio-temporal modeling, edge learning) using field data (traffic cameras, micromobility telemetry, connected vehicle/V2X, crash records, GIS). · Manage and coordinate pilot deployments
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projects. Experience integrating/interweaving qualitative inputs (e.g., policy, etc) with quantitative models and/or machine learning. Familiarity with MODFLOW, MATPOWER, OpenDSS, Machine Learning based
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