Postdoctoral Fellow in Scaling of Forest Structure using Remote Sensing: please find below further information about the job vacancy.
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.
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