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Field
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historical CORONA satellite imagery Integrate multi-source datasets including GEDI LiDAR and GLOBE citizen science observations Apply cutting-edge geospatial and statistical modeling techniques to quantify
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ability to program (e.g, python, R, and/or javascript). Must have at least some experience working with geospatial data. Preferred Qualifications, Competencies, and Experience Ability to develop impactful
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
ability to program (e.g, python, R, and/or javascript). Must have at least some experience working with geospatial data. Preferred Qualifications, Competencies, and Experience Ability to develop impactful
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area two, which focuses on integration of advanced data science with geospatial technologies to model environmental systems and predict climate impacts. Successful candidates will contribute
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learning applied to geospatial data Experience with Amazon Web Services or other cloud-based computing platforms Special Instructions to Applicants: For full consideration, applications must be submitted
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hydrologic connectivity metrics. Furthermore, the qualified candidate must possess advanced skills in geocoding, GIS, raster analysis/processing, and the management of large geospatial datasets. Familiarity
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expected to have experience in hydrologic/hydraulic modeling and in one or more of the following topics: in situ sensor installation and flood monitoring, GIS & geospatial big data, AI/ML and data science
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point cloud data processing, deep learning for time series data prediction, digital twin, geospatial mapping with vehicle and UAV mounted remote sensing systems or robotic systems, crowd simulation
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, Geospatial Science, Data Science, Computer Engineering, or a closely related field, with an emphasis on machine learning, AI, remote sensing, computer vision, or interdisciplinary data science applications
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. The expected base pay range for this position exceeds Stanford guidelines. Required Qualifications: PhD with substantial expertise in data science, geospatial techniques, and statistical/causal inference