Job no: 496393
Work type: Faculty, Non-Classified/Professional
Location: Boise, ID
|About Us:||Boise State University, powered by creativity and innovation, stands uniquely positioned in the Northwest as a metropolitan research university of distinction. Learn more about Boise State and the City of Boise at https://www.boisestate.edu/about/Boise State University is building an inclusive community of faculty and staff whose unique skills, cultural contributions, work history, and perspectives create a rich and rewarding academic experience for our students. Research demonstrates that people thrive when they feel welcome, respected, and inspired. We seek applicants who are committed to helping us achieve our vision of a diverse and inclusive community. Applications from members of historically marginalized groups, including women, BIPOC (Black, Indigenous, and People of Color), those with disabilities, members of the LGBTQ+ community, those who have served in the military, and members of other underrepresented communities are strongly encouraged.|
|Job Summary/Basic Function:||A Post-doctoral Research Associate position is available for a USDA-ARS-funded project focused on remote sensing of dryland vegetation in the western U.S. In particular, the post-doc will use uncrewed aerial systems (UAS) optical datasets, satellite data and AI (e.g. deep learning, machine learning) for quantifying vegetation and ground cover in dryland (rangeland) systems. These datasets will also be used to investigate pre- and post-fire responses (e.g. erosion) and recovery of vegetation communities. Sagebrush-steppe vegetation communities provide critical ecosystem services for biodiversity, habitat, carbon storage, and grazing in the Great Basin, USA. The post-doc will have the opportunity to develop and evaluate UAS protocols for data collection and data processing approaches for long-term monitoring as part of USDA-ARS Long-Term Agroecosystem Research (LTAR) programs.Our project team has rich geospatial datasets on dryland vegetation and we are looking for someone with advanced remote sensing, data science, and analytical skills to better monitor dryland vegetation in general, and sagebrush-steppe communities and their responses to climate change and land management. This project has strong potential for the post-doc to lead and be involved in high-impact peer-reviewed publications, to influence USDA ARS LTAR monitoring programs, and to develop a strong network of researchers.This position will be funded on a yearly basis, with up to 3 years of funding available. Although not guaranteed this position has the potential to be converted into a non-tenure track or a tenure track position in the future.|
|Department Overview:||The post-doc will join the BCAL community (https://www.boisestate.edu/bcal/) within the Department of Geosciences at Boise State University and the USDA-ARS Northwest Watershed Research Center in Boise, Idaho. Together we are a group of faculty, researchers and students committed to interdisciplinary studies in vegetation, soils, hydrology with remote sensing and other data analytics. Dr. Nancy Glenn (https://www.boisestate.edu/bcal/people/nancy-glenn/) will be the post-doc’s major advisor, and the post-doc will spend significant time with Drs. Pat Clark and Fred Pierson and the USDA-ARS team (Boise, Idaho) https://www.ars.usda.gov/pacific-west-area/boise-id/northwest-watershed-research-center/.|
|Level Scope:||After earning a Ph.D., the next step in the academic or research career path is often a postdoc. A postdoc is a continuation of a researcher’s training that enables them to further their professional development and start to transition from student to independent researcher. Postdocs also often take additional leadership or teaching responsibilities in their laboratory or department. These positions are usually two to three years and it is not unusual for a researcher to do more than one postdoc.|
|Essential Functions:||The project involves analyzing existing UAS data, planning and collecting new UAS datasets (multispectral and hyperspectral), and integrating with other types of remote sensing data (Sentinel, Landsat, Planet, SBG prototype, etc), strong coding skills, AI, and preparing manuscripts for publication in top-tier journals.|
|Knowledge, Skills, Abilities:||Expertise in data science, remote sensing, spatial analysis, ecology, hydrology, and/or modeling.|
Strong English written and verbal communication skills are required, as is the ability to work well in a team that includes interdisciplinary scientists and professionals.
Boise State University embraces and welcomes diversity in its faculty, student body, and staff. Accordingly, applicants who would add to the diversity and excellence of our academic community are encouraged to apply.
The selected candidate must be able to meet eligibility requirements for work in the United States at the time the appointment is scheduled to begin and to continue working legally for the proposed term of the appointment.
|Minimum Qualifications:||Competitive candidates will have a PhD, demonstrated expertise in using scientific programming language(s), and experience related to the topics above. We also welcome applications from candidates with a M.S. and a publication record in topics related to this research. Applicants that do not have a PhD are encouraged to reach out to Nancy Glenn ([email protected]).|
|Preferred Qualifications:||We are seeking a candidate with a publication record in using remote sensing datasets and spatial statistics for vegetation monitoring and analysis.|
|Salary and Benefits:||The salary for this position is $55,000 per year + full benefits. Boise State University is committed to offering a benefits package that provides health and financial protection plans as well as resources to promote health and well-being. Our program provides flexibility so you can choose the benefits that are right for you and your family. Learn more about our benefit options at https://www.boisestate.edu/hrs/benefits/.|
|Required Application Materials:||Applicants should apply with CV, contact information for 3 references, and a cover letter. The cover letter should include a statement describing experience with remote sensing, data science, and statistical techniques. We will review applications as we receive them and hope to hold preliminary interviews in February, 2022. The start date is flexible, but not later than Summer 2022. Informal inquiries about the position can be directed to Nancy Glenn ([email protected]).|
Advertised: January 13, 2022 Mountain Standard Time