The Poulsen Lab at Duke University (http://poulsenlabduke.com) is seeking an outstanding postdoc to study tropical forest ecology in Central Africa. The research will consist of two major foci: (1) Evaluation of how changes in the animal community cascade to affect forest structure, composition and services through the modification of ecological processes; (2) Quantification of tropical forest structure in relation to environmental and disturbance gradients. Specific topics include, but will not be limited to: seed and establishment limitation, seedling recruitment, forest dynamics, mangrove forest carbon, and plant-animal interactions.
The position will consist of supervising existing research projects in Central Africa, conducting brief training sessions in forest measurements, writing funding proposals, and analyzing data and writing papers. Approximately one-third of the position will involve overseeing research projects in French- speaking Africa. These will include data collection on mangrove carbon, estimation of forest biomass, and effects of plant enemies on tree recruitment. One-third of the position will consist of contributing to the analysis and writing of high impact manuscripts from existing datasets/projects. One-third of the position will entail creating and implementing novel research related to the above topics. 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. Because the fieldwork takes place in Central Africa, a basic knowledge of French is essential. Minimum Qualifications Required: Candidates must have obtained their PhD in ecology, environmental science, applied statistics or a related field by the appointment start date. Fluency in French is preferred. 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. Additional Qualifications 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 1.5-2 years, to begin as soon as possible. Interested applicants should apply through AcademicJobsOnline: https://academicjobsonline.org/ajo(See POSTDOC #7004). Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individuals age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.
