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Field
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. The Bush School also offers graduate certificates in Advanced International Affairs, Homeland Security, Nonprofit Management, Public Management, and Geospatial Intelligence, National Security Affairs
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to conduct biogeochemical and geomorphological research, including field data collection and analysis using remotely sensed imagery and geospatial data. The scholar will conduct scientific literature reviews
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research skills, particularly in statistical modeling, geospatial analysis, and health metrics evaluation. Experience working with a variety of spatial datasets, including remote sensing data, for health and
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. Candidates should have advanced skills in programming (e.g., R or Python) for processing and visualizing geospatial data, particularly time series of remotely sensed data, as well as ecological datasets
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and organizational skills Experience or interest in learning open source software design and data curation Experience in agricultural economics or agricultural policy (e.g. crop insurance) Geospatial
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relevant field. Ideal applicants will have experience in energy-system transition modeling, linear and mixed integer optimization programming, energy-related techno-economic assessment, and geospatial
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, Goldberg, and Kerr in order to advance their career in academic research, public health practice, and/or public policy. Important geospatial datasets used for this research include chemical transport
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
google earth engine). Must have experience working geospatial data. Preferred Qualifications, Competencies, and Experience Experience with optical satellite imagery, remote sensing of water quality
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
emphasis on remote sensing. 2. Experience of using multiple sources of remotely sensed data, particularly optical, Lidar, and Radar data. 3. Sound statistical skills and use of Machine Learning/Geospatial AI