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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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science, geospatial techniques, and statistical/causal inference Required Application Materials: CV 1-page cover letter describing research background and interests Stanford is an equal opportunity employer
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours 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
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, including familiarity with programming environments such as R or Python. Experience with geospatial analysis and/or systems modeling around agriculture/food/energy applications, as well as experience working
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postdoctoral position is available to work with a multidisciplinary team of researchers from the University of Maryland’s Center for Geospatial Information Science (CGIS ), National Center for Smart Growth (NCSG
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following areas: data management, survey methodology, multilevel regression, causal inference, machine learning, geospatial analysis. Preference is also given to applicants with research interests in one
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programming skills in Python or similar languages (e.g. Julia), and familiar with 1-2 industrial geospatial tools (e.g. SKUA-GOCAD, LeapFrog, ArcGIS, QGIS, or others). Being a quick learner with demonstrated
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MDBs/IFIs Strong publication record Experience working in participatory processes Experience in decision analysis and support processes Teaching experience Experience in geospatial modeling and GIS