We are excited to announce that we have a McIntire-Stennis funded Ph.D. position available in the Department of Forestry and Environmental Sciences at North Carolina State University (NCSU). This project will focus on loblolly pine growth response to fertilization across a gradient of soil types throughout the U.S. south using ancillary remote-sensed data such as LiDAR and/or NAIP imagery. In addition, the project will explore the range of response and the level of uncertainty in response to conduct an economic analysis focused on the return on investment of fertilizer application. This project seeks to connect the disciplines of soil science, biometrics, and economics. This research assistantship is currently funded for three years beginning in January 2022. Funding includes tuition, benefits, stipend, and equipment or travel funds needed to complete the project. There is a possibility of filling the position in August of 2021 with a person who could TA courses in forest mensuration and economics.
We want to welcome and encourage people from under-represented groups in forestry to apply. Raleigh is a diverse city that supports many different cultures and communities.
Please submit a CV and a statement of interest that outlines the qualifications which will make you successful in this position and the timeframe in which you are interested in starting (including when you are expected to graduate or when you completed your MS) by January 10th to Dr. Leah Rathbun at email@example.com.
The ideal candidate will have an M.S. or a B.S. with equivalent work experience in either physical resources (e.g., soils, geology, or geography), forestry (e.g., forest biometrics, management, or dendrochronology), and/or economics. This project will require a foundation in statistics (modeling and spatial data analysis), remote sensing (GIS and LiDAR), and economic theory. It is not expected that the incoming candidate be skilled in all these facets walking into the position but rather obtain some of these skills through coursework and mentoring during the project. Skills in R and/or Python are an advantage. The candidate will need good oral and written communication skills as they will be asked to present their findings in both presentations and peer reviewed journal articles.