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traps, statistical analysis of animal behavior, and GIS/geospatial analysis. The task of the new team member will be to capture and radio collar foxes and coyotes in and around the Twin Cities Metro Area
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
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within the past 3 years in Environmental Science, Geography, Computer Science, Atmospheric Sciences, or related field. Advanced GIS and geospatial computing expertise. Demonstrated commitment and ability
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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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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