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<span style="font-size:small;text-decoration-style:initial;text-decoration-color:initial;float:none;display:inline">Hi everyone,</span><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial">Please spread the word about this very exciting opportunity to work with the Natural Capital Project at Stanford University! A summary is below; find more info at <a href="https://careersearch.stanford.edu/jobs/remote-sensing-specialist-3371">https://careersearch.stanford.edu/jobs/remote-sensing-specialist-3371</a>.</div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><br></div><div style="font-size:small;text-decoration-style:initial;text-decoration-color:initial"><div>Geographic Info Systems Specialist 1</div><div>The Natural Capital Project, Stanford Woods Institute for the Environment</div><div>Job Family: Information Analytics</div><div>Job Series: Geographic Information Systems</div><div>Job Code: 4767</div><div>Grade: G</div><div>Exemption: Non-exempt</div><div>The Natural Capital Project is a partnership among Stanford University’s Woods Institute for the Environment, University of Minnesota’s Institute on the Environment, The Nature Conservancy, and World Wildlife Fund. We develop tools to model and map the distribution of biodiversity and the flow of multiple ecosystem services (ES) across land- and seascapes. </div><div><br></div><div>We seek a creative and talented remote-sensing expert for a Geographic Information Systems Specialist position to advance the use of remote-sensing in our ES models. With remotely-sensed indicators of ecosystem condition, phenology or biomass, and other ecosystem characteristics such as soil moisture becoming available at increasingly fine resolutions and broad extents, ES tools should be adapted to make better use of this information. Cutting-edge approaches to derive ecosystem structure and function from continuous variables could be mainstreamed into ES tools, to replace or augment inputs currently represented by categorical land-use information. This position will identify useful data sources derived from remote-sensing, perform routine spatial data analyses and derive new products where necessary, test these products against observed data, create and maintain spatial databases of remote-sensing inputs to ES models, and prepare maps and graphics using a variety of geospatial software and graphic applications. Please note this position is fixed-term for 18 months with a possibility of reappointment based on programmatic and funding needs.</div></div></div>