PhD Assistantship: Species distribution modeling of intraspecific variation
The University of Maryland Center for Environmental Science is seeking a motivated PhD student interested in studying intraspecifc variation in forest tree phenology and its relationship to underlying genomic variation and environmental gradients. The student would join a team of biogeographers, remote-sensing scientists, and population geneticists to develop novel statistical methods to model and map intraspecific variation at regional to continental scales. An emphasis of the position is on developing approaches to identify the geographic location of populations pre/mal-adapted to future climate change. Within this framework, there are numerous opportunities for a student to extend the broader project objectives to include any number of ideas the student is most interested in pursuing. This is an ideal project for an individual with excellent quantitative and computer programming skills (e.g., R, python, etc.) and with an interest in working at the interface of biogeographical modeling, remote sensing, and landscape genomics, while developing the following skills: - statistical modeling generally and spatial modeling of biodiversity in particular - remote sensing of phenology - spatial analysis, including GIS - macroscale ecology and global change The project is based at the Appalachian Laboratory in Frostburg, Maryland, with Matt Fitzpatrick, Andrew Elmore, and Stephen Keller. Student support has been secured through a grant from the National Science Foundation. The student will matriculate through the Marine, Estuarine, and Environmental Sciences Program (MEES) at the University of Maryland, College Park and will reside at the Appalachian Laboratory in Frostburg for the duration of the project. To apply, please email as a single pdf document: (1) a statement of interest, (2) a CV, and (3) contact information for three referees to [email protected]. Review of applications will begin on February 18th, 2013 and will remain open until filled. Position start date is Fall 2013.
