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Field
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: A Ph.D. (by the start date) in Remote Sensing, Geography, Biology, Geospatial Science, Environmental Science
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based on empirical studies and/or model simulations. The candidate should assemble and evaluate quantitative proxy reconstructions, and apply geospatial and/or numerical modeling methods to investigate
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Sensing, Geospatial Science, Environmental Science, Data Science, or related field. Strong background in remote sensing data analysis, image processing, and geospatial analysis. Experience working with
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present results at conferences and workshops. Mentor master students and PhDs Qualifications: Ph.D. in Remote Sensing, Geospatial Science, Environmental Science, Data Science, or related field. Strong
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make a difference in the world! Position Information Texas A&M AgriLife Research at Temple is seeking a highly motivated scientist with expertise in areas of crop modeling, remote sensing, geospatial
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qualifications: Experience creating informative web-based data visualization, especially with geospatial data (e.g. maps). Successful candidates will be expected to lead and collaborate on research projects full
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Science, Geospatial Science, or a related field. Experience processing satellite imagery (Sentinel-2, Landsat/HLS), including atmospheric correction, cloud masking, and geometric/radiometric preprocessing
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of Aalborg University. Job Description This position is part of the cross-disciplinary DK-Future project – Probabilistic Geospatial Machine Learning for Predicting Future Danish Land Use under Compound Climate
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on human trafficking, including supply chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data
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CONUS EPIC model into the current version of EPIC. Support the tool development (e.g., programs, macros, SQL queries) to systematically upgrade the geospatial and tools in the CONUS EPIC integrated with