Description
About the position:
The research group of Dr. Sydne Record (https://sites.google.com/maine.edu/record-lab) seeks applicants for one Ph.D. position in Ecology and Environmental Sciences at the University of Maine in Orono in the Department of Wildlife, Fisheries, and Conservation Biology starting in September 2024. 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. We are a highly collaborative group that values team science.
Responsibilities
Partial funding for this assistantship comes from the Northeastern States Research Cooperative to map forest connectivity for wildlife using theory and remote sensing. This project will utilize in-situ data from the United States Forest Inventory and Analysis and the National Ecological Observatory Network (NEON) and imagery from the National Aeronautics and Space Administration, NEON, and the United States Department of Agriculture, among others. While the specific directions for dissertation research are open to the student’s interests, we anticipate topics related to size-abundance scaling, community assembly, and life history theory that can be applied to understand patterns of biodiversity and important corridors for wildlife habitat connectivity. This is project is primarily devoted to computational work, but there will be opportunity for some field work to ensure that models are grounded in reality. We anticipate a final dissertation comprised of four chapters suitable for submission to peer-reviewed journals, as well as the opportunity to contribute as a co-author on other manuscripts completed as part of the collaborative research.
Qualification
Required Qualifications: We seek applicants with a B.S. in biology, ecology, environmental data science, or other relevant discipline with a G.P.A. >3.0. The ideal applicant will have quantitative skills (e.g., R, Python, geographic information systems) and interest in learning new skills, previous research experience and a strong background in ecology and environmental science, creativity, and an excellent track record in seeing projects through from start to finish. Successful applicants will be expected to work both independently and collaboratively, mentor undergraduates in the group, develop independent research questions related to overall project goals, and publish research results. Good oral and written communication skills and flexibility given the unexpected nature of research are highly valued. We are committed to anti-racism and value diverse identities, experiences, and skills.
Desired Qualifications: Preference will be given to applicants with experience or demonstrated interest in field ecology and quantitative methods, ideally with a M.S. in environmental data science or ecology. Preferred applicants will show evidence of publishing from their prior research or M.S. thesis. Preference will be given to applicants who have a strong record of communication as evidenced by conference presentations and prior team science collaborations. Prior experience or exposure through coursework with the following quantitative skills: GIS, spatial analysis, processing of remotely sensed data, machine learning, and maximum likelihood and/or Bayesian estimation methods. Experience using R and/or Python for data management, analysis, and presentation of results.
Link: https://lnkd.in/gtUxprkj
Lab: https://lnkd.in/gCWaAhda
Contact: Email sydne.record@maine.edu with the subject line “Quantitative Ecology PhD Assistantship” if you have questions.
