Smithsonian Postdoctoral Fellowship: Grassland Remote Sensing in Mongolia
The Smithsonian Conservation Biology Institute (SCBI)- Conservation Ecology Center (https://nationalzoo.si.edu/conservation-ecology-center ) is seeking a Postdoctoral Fellow starting in Spring 2022.
The NASA-funded three-year fellowship focuses on advancing SCBI’s remote sensing and grassland research capacity. This multi-disciplinary project seeks to collect and analyze a large quantity of unmanned aerial vehicle (UAV) data in the Mongolian steppe systems and integrate it with time-series mid-resolution spaceborne optical remote sensing data (e.g., Landsat/Sentinel/HLS) to explore how the data fusion can improve mapping of vegetation functional types in grassland systems in Mongolia.
The awardee is expected to develop innovative research on collecting and processing large volumes of UAV data to create novel and scalable methods to characterize percent cover of various vegetation functional types over broad areas and explore how the new information can improve the existing understanding of the social and economic impact of rural out-migration in Mongolia. This position is unique because it relies on both satellite and UAV remote sensing datasets and will be an integral part of an interdisciplinary collaboration that integrates quantitative remote sensing data with qualitative interview and survey data on the ground.
In addition to the primary research responsibility, the awardee will have the opportunity to
- Assist with organizing household surveys and interviews in Mongolia
- Collaborate with additional team members based at the George Washington University, the University of Montana, the Wildlife Conservation Society in Mongolia and other organizations in Mongolia.
- Contribute to and develop collaborative spatial ecology proposals and research projects.
- Engage in teaching professional master-level GIS/Spatial Ecology courses at Smithsonian Mason School of Conservation.
- Mentor student interns/fellows at SCBI.
The position will remain open until filled, with the desired start date of April-May 2022. Reviewing of the applications will start on January 10, 2022.
Awardee benefits include:
- Annual salary starting at $60,000
- Smithsonian trust employee healthcare and retirement benefit.
Qualifications:
The successful candidate must have a Ph.D. in Physical Geography, Remote Sensing, Environmental Sciences, Computer Science, Ecology, or a related field by the start date of the position. Must be able to work independently yet collegially in a team environment.
Specifically, we look for candidates with:
The Smithsonian Conservation Biology Institute is located at the north entrance of the Shenandoah National Park, about 60 miles west of Washington, D.C., in Front Royal, VA. SCBI’s mission is to advance the conservation of biological diversity. In meeting the Smithsonian Institution’s mandate, SCBI increases knowledge through investigations of threatened species, habitats, and communities and disseminates knowledge through advanced studies, professional training, and public outreach.
This position is subject to the Smithsonian’s background check policy. The candidate will be required to travel to Washington D.C. at least once for background check purposes. However, there will be flexibility for telework options during the pandemic. The awardee is expected to be relocated to Front Royal when the SCBI office reopens.
The SOLAA application system will be open until the position is filled. Interested applicants should submit their cover letter (stating preferred starting time), CV, and the names and contact information of 3 references (reference letters will only be requested when applicants are shortlisted) on the Smithsonian SOLAA system. To apply, you need to register on the Smithsonian SOLAA system (https://solaa.si.edu/solaa/#/public ) and search for “Postdoctoral fellowship” under “National Zoological Park”. The program name is “Spatial Ecology Postdoctoral Fellowship”. Questions about the position can be addressed to Dr. Qiongyu Huang ([email protected]).
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