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, digital twin, geospatial mapping with vehicle and UAV mounted remote sensing systems or robotic systems, crowd simulation, reinforced learning, flood modeling and impact analysis, complex system modeling
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at very high spatial resolution. The candidate will collaborate closely with the Remote Sensing and Hydrology lab and the Rutgers Infrastructure Resilience Group. Both groups involve a number of research
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for flood risk estimation, and prototyping flood monitoring and forecasting procedures at very high spatial resolution. The candidate will collaborate closely with the Remote Sensing and Hydrology lab and the
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NSF, FEMA, DHS, and other local agencies. They will lead research activities involving harnessing and synthesizing the latest developments in artificial intelligence, remote sensing, and simulation and
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essential to the project. Also, the integration of remote sensing data for analysis with ground-truth data will be useful. The applicant must be able to comply with high standards of work ethics, regulations
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team and complete projects without constant supervision. Understanding the complexity of ecological data sets and the analysis thereof is essential to the project. Also, the integration of remote sensing