Duke University, Nicholas School of the Environment - Durham

2864 24228
Position ID:Duke-NSOE-Durham-POST_POULSEN [#24228, 3820]
Position Title: Postdoctoral Associate - Quantitative Interdisciplinary Ecology
Position Type:Postdoctoral
Position Location:Durham, North Carolina 27708, United States [map] sort by distance
Subject Areas: Ecology / Quantitative Ecology
Climate and Health
Environmental Science
Appl Deadline: (posted 2023/01/27, listed until 2023/07/27)
Position Description:    

Postdoctoral Researcher in Quantitative Interdisciplinary Ecology

The Poulsen Lab at Duke University (http://poulsenlabduke.com) is seeking an outstanding postdoctoral researcher (PR) to contribute to two exciting projects: (1) Climate-Health in the Kafue Ecosystem, and (2) Pathogens to Pachyderms. Although distinct, both projects incorporate modeling forest structure through field measurements and terrestrial LiDAR in relation to natural and human disturbances.

The first project, Climate-Health in the Kafue Ecosystem, is a new interdisciplinary project funded by the Duke Expeditions program with the goal of linking climate change with human health to alleviate adverse human health impacts in western Zambia. This project focuses on four growing health threats - respiratory illness, malnutrition, water-borne illness, and vector-borne disease. For each of these threats, the aims are to: (1) identify the direct and indirect mechanisms linking climate change with human health, (2) determine the effectiveness of interventions, such as fire management and health education, in mediating the effects of climate change on human health, and (3) quantify whether interventions which effectively reduce deforestation can positively impact both environmental and health outcomes simultaneously. This project partners scientists with practitioners to design and implement a scientifically rigorous program with applied conservation and health goals.

The second project, Pathogens to Pachyderms, is an ongoing NSF-funded project to evaluate the impacts of animals species on forest structure and diversity in tropical forest in Gabon. By following change in vegetation across eights experimental sites, the project aims to: (1) assess the relationship among trees and the organisms with which they interact over plant life stages, including fungi, insects, and terrestrial mammals; and (2) quantify the degree to which defaunation alters these plant-animal interactions and tree recruitment. The position entails working with a dynamic, interdisciplinary team – including practitioners, health experts, social scientists, and ecologists. The PR will work in collaboration with the PI to ensure project implementation and management. There will be opportunities to visit the project sites in Zambia and Gabon to train field teams in methods and to evaluate rigor in data collection. A primary responsibility of the position will be the management and analysis of ecological and health data and the writing of high impact manuscripts. In addition, the PR will have opportunities to collaborate on grant writing and to mentor American and African undergraduate and graduate students. As such, we are looking for candidates with field experience, very strong quantitative, programming, and modeling skills, and a demonstrated ability to write and publish.

Minimum Qualifications Required: • PhD in ecology, environmental science, forestry, applied statistics or a related field obtained by the appointment start date. • Strong statistical and programming skills in R, with the ability to analyze data from different disciplines like health and ecology. • Knowledge of GIS, remote sensing, and spatial modeling. • Project management skills, including strong communication skills, ability to work with and guide multiorganization teams, experience organizing data collection teams and overseeing research assistants. • Writing skills, as evidenced by a record of publication. • Ability to work well independently and as a part of a team.

Additional Qualifications • Previous experience working a terrestrial LiDAR scanner, processing and analyzing data. • Experience with Bayesian analysis and fitting of maximum likelihood models. • The best-qualified applicants will also have exceptional reasoning and analytical skills, and experience working as part of an interdisciplinary team of scientists.

The appointment is for 2 years, to begin as soon as possible.

Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.

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