Description

Pending final approval from USDA, approximately 2.5+ years of funding will be available at the UNIVERSITY OF DELAWARE’S (UD) Department of Entomology and Wildlife Ecology for a graduate research assistant (M.S. or Ph.D.). The student will help conduct research on a multidisciplinary project to better quantify waterfowl (dabbling duck and geese) daily movement patterns on the Delaware/Maryland Peninsula and build a near-real-time waterfowl mapping web application for Avian Influenza Virus (AIV) surveillance to improve food security in commercial poultry in the Mid-Atlantic. This research will occur in collaboration with the University of California-Davis and USGS. Project objectives include 1) collecting and analyzing fine scale GPS telemetry data of waterfowl movement and distributions in relationship to landscape variable, 2) connecting and predicting waterfowl movement patterns with weather surveillance radar and other remote-sensing data, 3) sampling water, sediment, and waterfowl for AIV, 4) testing for correlation between AIV and waterfowl distributions, and 5) building a near-real-time waterfowl mapping web application. Additionally, we encourage the student to focus on any component/s of the project for their own thesis/dissertation research. This is a great opportunity to engage in cutting-edge radar aeroecology research in the area of One Health within a top-notch Wildlife program. The student will be co-advised by Dr. Jeff Buler and Dr. Chris Williams within UD’s Aeroecology (https://sites.udel.edu/aeroecologyprogram/) and Waterfowl and Upland Gamebird programs (http://canr.udel.edu/faculty/williams-chris/). 

Requirements

Qualified applicants should have a B.S. in Zoology or Wildlife Ecology, a minimum 3.2/4.0 GPA, and a minimum combined math/verbal GRE score of 300. Experience with GIS, telemetry, and R is preferred. Additionally, we seek candidates with prior experience/knowledge in one or more areas of waterfowl ecology, avian disease ecology, poultry science, or radar aeroecology. This work will involve a mix of some fieldwork and mostly computer work (possibly lab work if so desired). Therefore, it is critical that a successful applicant have a penchant for quantitative data analysis and computer modeling of large remotely-sensed datasets.

Apply: Send a cover letter outlining experience and research interests, curriculum vitae, unofficial copies of university transcripts and GRE scores, and contact information for three references