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The Department of Forest Ecosystems and Society invites applications for a full-time (1.0\u00a0FTE<\/span>), 12-month, Faculty Research Assistant position. Reappointment is at the discretion of the Department Head.<\/p>\n The College of Forestry at Oregon State University actively develops new techniques for interpreting remotely sensed data from a variety of space-based platform, and applies those techniques to better understand forest ecosystems. Particular areas of interest include: forest structure mapping; forest carbon estimation; species distribution modeling; quantifying forest fragmentation; lidar; mapping historical fires and harvests; deforestation hotspot warning systems; and forest albedo. This position will provide a range of geographic programming services supporting the above research interests. The Faculty Research Assistant will develop automated workflows with remotely sensed imagery to track the condition and trends of forests around the world. The position involves statistical analysis, contributing to and writing manuscripts, and collaboration with a variety of partners.<\/p>\n 100% \u2013 Research:<\/strong> Qualifications<\/strong><\/p>\n \u2022 B.S. in computer science or B.S. in a natural resource field with strong, demonstrated record of geographic programming.<\/p>\n \u2022 Exposure to python, R, and Javascript.<\/p>\n Preferred<\/strong><\/p>\n \u2022 M.S. or Ph.D. in computer science or a natural resource field with strong, demonstrated record of geographic programming.<\/p>\n \u2022 Experience in developing complex scripts in python, R, and Javascript.<\/p>\n \u2022 Experience in database management<\/p>\n \u2022 Experience in developing user interfaces.<\/p>\n \u2022 Experience with Google Earth Engine.<\/p>\n \u2022 Demonstrable commitment to promoting and enhancing diversity.<\/p>\n <\/p>\n
\n\u2022 Develop code to process a variety of remote sensing data, including Landsat and spaceborne lidar and radar sensors. Processing may occur locally or on cluster- or cloud-based platforms.
\n\u2022 Analyze alternative mapping approaches, quickly summarizing diagnostic information related to map accuracy and model properties.
\n\u2022 Use geographic information systems to summarize ecological implications of new maps and other satellite-derived datasets.
\n\u2022 Implement species distribution models and mapping at broad spatial scales.
\n\u2022 Manage forest inventory and geographic data across a variety of platforms.
\n\u2022 Suggest creative improvements to current procedures.
\n\u2022 Create user interface resources for newly developed information.
\n\u2022 Contribute to or lead writing manuscript for research findings.
\n\u2022 Documentation of the above.<\/p>\n