Natural Sciences Environmental Sciences/Ecology/Forestry Earth Sciences Botany/Plant Sciences Biology - General Sciences - General
The Poulsen Lab at Duke University is seeking an outstanding postdoc to contribute to a NSF-funded project. The goal of the project is to test the hypothesis that depletion of megafauna, specifically African forest elephants, in tropical forests has cascading effects on remaining fauna and flora, destabilizing forest dynamics.
The research objectives are to:
(1) assess the relationship among trees and the organisms with which they interact over plant life stages, including fungi, insects, and terrestrial mammals;
(2) quantify the degree to which defaunation alters these plant-animal interactions and tree recruitment; and
(3) generate individual based models to simulate population dynamics of elephant-dispersed tree species to compare extinction probability in simulated populations with and without elephants.
The position will consist of setting up large-scale experiments and data collection in the field Central Africa and analyzing data and writing scientific publications. Approximately one-half of the position will involve working in French-speaking Africa. One-half of the position will consist of data analysis and writing of high impact manuscripts from existing and new datasets. The successful candidate will also have the opportunity to mentor undergraduate and graduate students.
As such, we are looking for candidates with good field skills, strong quantitative, programming, and modeling skills, and a demonstrated ability to write and publish. A basic knowledge of French is helpful, but not necessary.
Minimum Qualifications Required:
Candidates must have obtained their PhD in ecology, environmental science, applied statistics or a related field by the appointment start date.
Strong statistical and programming skills in R are essential.
Demonstrated writing skills, as evidenced by a record of publication, are necessary.
Candidates must demonstrate the ability to work well independently and as a part of a team.
Ability to work in remote, rainforest conditions (buggy, high humidity, precipitation and temperatures).
Ability to walk 6-10 miles in a day carrying a 25 pound backpack.
Experience with Bayesian analysis and fitting of maximum likelihood models is preferred.
Familiarity with GIS is beneficial.
The best-qualified applicants will also have exceptional reasoning and analytical skills, and experience working or ability to work as part of an interdisciplinary team of scientists.
The appointment is for 2 years, to begin as soon as possible.
The cover letter should identify relevant experience and skills, potential start date, interests in relation to the above description, and how this opportunity fits into the applicant’s longer-term goals. The cover letter should also include the names and contact information of up to three people who can provide letters of reference.
We look forward to hearing from you!
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