We are about to start a really fun project that includes both remote sensing- and field-based research in one of the most interesting marsh systems in California. Can you please pass this opportunity along to potential applicants?
Postdoctoral Scholar in Hyperspectral Remote Sensing of Invasion Ecology
A full-time postdoctoral scholar position in hyperspectral remote sensing of invasion ecology is available at the University of California Merced. The focus of this research is to study the ecosystem engineering impacts of water primrose (Ludwigia spp.) in the Sacramento-San Joaquin Delta, the landward end of the San Francisco Estuary. Water primrose is a highly invasive, non-native floating macrophyte in that, in recent years, has extended its niche into marsh habitat, causing extensive mortality of marsh vegetation. The goals of the project are to understand how water primrose invades and overtakes marsh as well as the factors that make marshes vulnerable to invasion. Hypothesized mechanisms include water primrose traits associated with growth strategy, its allelopathic properties, or factors related to marsh community structure. The postdoctoral scholar will carry out research to map and quantify the spatial trajectory of marsh loss due to invasions and implement and develop research ideas to model and map landscape-level marsh loss vulnerability due to invasion with the guidance of the PI and Science Team. The postdoctoral scholar is expected to conduct field sampling for plant traits and community structure as well as analyze hyperspectral imagery collected from both piloted aircraft and UAV platforms.
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The postdoctoral position will be in the Earth Observation and Remote Sensing Lab in the Department of Civil & Environmental Engineering at UC Merced. The postdoctoral scholar will be based in Merced, California and will work under the supervision of the PI, Dr. Erin Hestir, in close collaboration with Dr. Shruti Khanna from California Department of Fish and Wildlife (CDFW) and scientists from the United States Geological Survey (USGS).
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The University of California, Merced, is the newest of the University of California system’s 10 campuses. With 8,500 undergraduate and graduate students (https://www.ucmerced.edu/fast-facts), UC Merced provides outstanding educational opportunities to highly qualified students from the heart of California, the nation, and abroad. The campus has special connections to nearby Yosemite National Park; is on the cutting edge of sustainability in construction and design; and supports the economic development of Central California. The Merced 2020 Project doubled the physical capacity of the campus, and enhanced academic distinction, student success, and research excellence (https://merced2020.ucmerced.edu/).
Qualifications:
A Ph.D. (at the time of appointment) in the physical sciences (ecology, plant biology, geography, environmental science, etc.) or engineering (environmental, aerospace, optical) with a focus on ecological remote sensing, geospatial analytics or ecological modeling. Expertise in hyperspectral remote sensing, landscape ecology, and spatial modeling is ideal. The successful candidate will have demonstrated strong collaborative skills and will have at least 1-2 first author peer review research papers.
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Technical skills include proficiency in programming for remote sensing image analysis, statistical modeling, graphics and visualization (e.g., Python, R, javascript), shell scripting and Linux command line tools. The ideal candidate will have experience with high performance computing for image processing, particularly for imaging spectroscopy, and geospatial analysis.
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To Apply:
Interested applicants are required to submit 1) a cover letter indicating research interests and experience, 2) curriculum vitae, and 3) a list of three references with contact information including mailing address, phone number and e-mail address submitted through AP Recruit during the application process.
https://aprecruit.ucmerced.edu/JPF01007
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For more information, please contact Dr. Erin Hestir at ehestir@ucmerced.edu