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2.5 year Postdoc UMaine or Remote
Job Description
- Agency
- University of Maine
- Location
- Orono, ME or Remote
- Job Category
- Post Doctoral Appointments
- Salary
- $50,000-54,000
- Start Date
- 09/01/2023
- Last Date to Apply
- 05/01/2023
- Website
- https://umaine.hiretouch.com/job-details?jobID=80771&job=postdoctoral-research-associate-remote-sensing
- Description
- Postdoctoral Fellow Scaling of Forest Structure using Remote Sensing University of Maine, Orono in the Department of Wildlife, Fisheries and Conservation Biology The research group of Dr. Sydne Record (https://sites.google.com/maine.edu/record-lab/home) seeks applicants for one postdoctoral fellow at the University of Maine in Orono in the Department of Wildlife, Fisheries, and Conservation Biology starting September 1, 2023 or earlier. Our research group focuses on population and community ecology from a biogeographical perspective. We apply computational methods to data from various environmental observatory networks to explore ecological dynamics across space and time. Funding for this position comes from a National Aeronautics and Space Administration grant. The postdoctoral researcher will conduct research to incorporate disturbance through time and remote sensing into a scaling framework of forest structure and functional diversity using in-situ and remotely sensed data. This position is fully funded for up to 30-months pending satisfactory performance. Our research group is committed to anti-racism and values diverse perspectives. Applicants from historically excluded groups are encouraged to apply. Qualifications: A Ph.D. in ecology, geography, or environmental data science. Experience with management of big data sets (e.g., USFS Forest Inventory and Analysis, remotely sensed data, such as LiDAR), analyses in R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. The ideal applicant will also have a strong background in forest ecology and life history theory, creativity, a strong publication record, and an excellent history in seeing projects through from start to finish. Successful applicants will work well both independently and collaboratively, mentor undergraduate and graduate students, and publish and present research results. This is project involves computational work and minimal field work. Good oral and written communication skills and flexibility given the unexpected nature of research are highly valued. Hiring of the selected candidate will be conditional on a background check performed by the UMaine Office of Human Resources. Location: The University of Maine Orono campus is a community of ~12,000 undergraduate and graduate students. UMaine is in beautiful central Maine with an excellent quality of life (little traffic, reasonable cost of living, safe neighborhoods). Outdoor recreational activities abound with Mount Katahdin (Baxter State Park) and Acadia National Park within one hour drive and fifteen miles of running, biking, and cross-country skiing trails on campus. Closing date: review of applications is ongoing, open until filled. Contact: Please apply at https://umaine.hiretouch.com/job-details?jobID=80771&job=postdoctoral-research-associate-remote-sensing . Email sydne.record@maine.edu with the subject line “NASA Postdoc” if you have questions. The University of Maine Orono is an EEO/AA employer, and does not discriminate on the grounds of race, color, religion, sex, sexual orientation, including transgender status and gender expression, national origin, citizenship status, age, disability, genetic information or veteran’s status in employment, education, and all other programs and activities.
- Qualifications
- Qualifications: A Ph.D. in ecology, geography, or environmental data science. Experience with management of big data sets (e.g., USFS Forest Inventory and Analysis, remotely sensed data, such as LiDAR), analyses in R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. The ideal applicant will also have a strong background in forest ecology and life history theory, creativity, a strong publication record, and an excellent history in seeing projects through from start to finish. Successful applicants will work well both independently and collaboratively, mentor undergraduate and graduate students, and publish and present research results. This is project involves computational work and minimal field work. Good oral and written communication skills and flexibility given the unexpected nature of research are highly valued. Hiring of the selected candidate will be conditional on a background check performed by the UMaine Office of Human Resources. Application review is rolling. Open until filled.
- Contact Person
- Sydne Record
- Contact eMail
- sydne.record@maine.edu
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