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subsidized housing at Kent Vale. Qualifications Successful candidates should be actively engaged in landscape architectural research and design, including but not limited to geospatial analysis, landscape
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within the scope of Own funding for the development of R&D projects of FCiências.ID, under the following conditions: Scientific Area: Geospatial Engineering Admission requirements: Degree in Geospatial
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transport; specialization: cartography, spatial information systems, geoinformation, geospatial engineering or related fields; experience in acquiring, processing, analyzing, verifying and visualizing spatial
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; specialization: cartography, spatial information systems, geoinformation, geospatial engineering or related fields; experience in working with spatial data; skills in automating spatial data processing processes
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sensing-based flood detection and mapping, and geospatial modeling. Two (2) years of postdoctoral experience in related research. Background Investigation Statement: Prior to hiring, the final candidate(s
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Modeling and Geospatial Analysis. Two (2) years of postdoctoral experience in related research. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre
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degradation in the Guadalupe River, Texas. The project guides an undergraduate student to participate in the scientific discovery process by integrating various geospatial datasets and apply innovative remote
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Environmental Science, Physics, Mathematical Sciences, Geospatial Sciences and Computer Science (Information Technology and Software Engineering). One of RMIT's top-performing research schools, we deliver
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of research outcomes to end users, including potential commercialisation of UQ intellectual property. Review and apply best-practice research methodologies in geospatial data science and climatology
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
. Integrate independent references for rigorous validation. Methods & Data Engineering Design generalizable, well-documented pipelines for data fusion and modeling using established geospatial and scientific