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Ph.D. Opportunity in Forest Ecology – University Maryland

October 12, 2016
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Ph.D. position,  Swenson Lab at the University of Maryland

The Swenson Lab at the University of Maryland (http://www.swensonlab.com) is seeking to add a new Ph.D. student to begin in the fall of 2017.

Swenson Lab is looking for a student interested in conducting highly interdisciplinary research working with concepts and techniques from forest ecology, transcriptomics, physiological ecology, and demographic modeling.

Previous experience with quantitative analyses in ecology and/or genetics are preferred, but are not a requirement. A passion for and dedication to research are essential as is an integrative approach to tackling big problems.

The researcher would be a part of a larger project in the Swenson Lab that recently received NSF funding, but the student would be encouraged and expected to develop novel avenues of investigation that can leverage the design, samples and data generated from the larger project. The student would also be expected to assist in field research at two study sites: Harvard Forest & the Smithsonian Environmental Research Center.

The lab is located in the Department of Biology (http://biology.umd.edu) at the University of Maryland with a Ph.D. student concentration in our Behavior, Ecology, Evolution and Systematics program (http://www.bisi.umd.edu/bees/).

Existing collaborations with the Smithsonian, particularly with the Center for Tropical Forest Science (http://www.forestgeo.si.edu) and the Smithsonian Environmental
Research Center (https://serc.si.edu), our proximity to the National Museum of Natural History (http://www.mnh.si.edu) and collaborative relationships with the National Socio-Environmental Synthesis Center (http://sesync.org) in Annapolis allow students in the lab to interact in a broader scientific community in the DC area.

If interested, please email Nate Swenson (swenson@umd.edu) with a brief statement of  your interests and research experience, GRE scores if available, GPA and list of biology, statistics, and/or mathematics courses taken.

Students from under-represented groups in ecology and evolution are particularly encouraged to apply.

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