A MS graduate student assistantship is available in the area of 
socioeconomic-ecological 
systems modeling. The student will work on an EPA-funded interdisciplinary 
project led by 
Dr. Jacob Hochard (Dept. of Economics & Institute for Coastal Science and 
Policy) in 
collaboration with Drs. Randall Etheridge (Dept. of Engineering & Center for 
Sustainability) 
and Ariane Peralta (Dept. of Biology) at East Carolina University. The MS 
student will work 
closely with economics, biology and engineering faculty at East Carolina 
University, as well 
as a PhD student in Coastal Resources Management. The qualified candidate will 
have 
strong undergraduate training in ecology, biogeochemistry, or environmental 
science. 
Ideally, the student will have some knowledge of GIS, hydrology, and 
biogeochemical 
processes. Candidates with an interest in interdisciplinary research and a 
familiarity or 
willingness to learn social-ecological modeling approaches are encouraged to 
apply. The 
project will be focused on modeling relationships between biophysical factors 
and water 
and air quality on human health outcomes to understand how natural capital can 
contribute 
to nutrient pollution mitigation in coastal watersheds. Visit 
www.peraltalab.com for more 
information.
 
To apply, please contact Drs. Ariane Peralta (peral...@ecu.edu) and Randall 
Etheridge 
(etheridge...@ecu.edu) with your CV, unofficial transcript(s), GRE scores, and 
a short 
statement describing prior research experience and interests. Review of full 
applications to 
the MS biology program 
(http://www.ecu.edu/cs-cas/biology/BiologyGrad/index.cfm) will 
begin on February 15, 2017 and will continue until the position is filled.
 
The Departments of Biology, Economics, Engineering, Institute of Coastal 
Science and 
Policy, and the Center for Sustainability at East Carolina University take 
pride in the 
diversity of our students, faculty, and staff and strive to increase that 
diversity. We 
encourage applications and inquiries from members of groups underrepresented in 
the 
natural sciences.

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