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policy, agronomy, or a related field Desired Qualifications Strong skills in satellite remote sensing, GIS, and statistical analysis. Experience using cloud-based computing resources (e.g. Google
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grassland ecosystems, b) integrate remote sensing data (e.g., NDVI, EVI, land surface temperature) with eddy flux measurements to scale up findings and develop predictive models of water use efficiency
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, Movebank), remote sensing data, GIS tools and quantitative/spatial approaches including machine learning to understand how wildlife species are reacting to climate change at continental or global
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modelling and statistical software such as R, Python, or MATLAB. Experience using GIS, side-scan sonar, multibeam bathymetry, underwater imagery, remote sensing, and other marine habitat mapping
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modelling and statistical software such as R, Python, or MATLAB. Experience using GIS, side-scan sonar, multibeam bathymetry, underwater imagery, remote sensing, and other marine habitat mapping
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modelling and statistical software such as R, Python, or MATLAB. Experience using GIS, side-scan sonar, multibeam bathymetry, underwater imagery, remote sensing, and other marine habitat mapping
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sensing and open-source GIS tools (e.g. Google Earth Engine) Expertise related to climate change, meteorology, terrestrial ecology, physiology, or conservation decision-making Equipment Utilized
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include experience with: GPS telemetry and animal movement analyses. Geospatial analysis, GIS, and remote sensing. Statistical, ecological, and machine-learning modeling using modern analytical
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. Experience working with global livestock, land-use, climate, remote-sensing. Satellite images, or sustainability indicator datasets. Competence with GIS tools and spatial analysis software. Experience with
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. Experience working with global livestock, land-use, climate, remote-sensing. Satellite images, or sustainability indicator datasets. Competence with GIS tools and spatial analysis software. Experience with