The World Wildlife Fund is hiring a Postdoc focused on wildlife connectivity. S/He will be analyzing data from the KAZA utilizing new models, with data coming from a variety of different species. Applicants should be familiar with programs such as ArcGIS, R, and Circuitscape. Experience with wildlife conservation in southern Africa is preferred.
World Wildlife Fund, the global conservation organization, seeks a dynamic and motivated quantitative Post-doctoral fellowship – movement ecology & wildlife connectivity associate to lead analyses related to assessing wildlife connectivity in the Kavango-Zambezi (KAZA) transfrontier conservation area in southern Africa. The individual will take up the Mark Schell Research Fellowship at WWF-US and will be responsible for developing statistical models and metrics of connectivity that will allow conservation planners and other stakeholders in the region to manage a suite of large wildlife species in the central part of KAZA.
This is a one-year, fixed term position that will involve working closely with WWF's Lead Scientist for Wildlife Conservation, as well as other research team members in Namibia and Botswana. The position is based in WWF's Washington DC, but will require frequent communication with other team members as noted above.
- Analyzes movement data from a variety of wildlife species in the central part of KAZA, using state of the art movement models (step selection functions, path selection functions, etc)
- Develops movement resistance layers across the KAZA region using ArcGIS and R
- Uses Circuitscape or related programs and algorithms to produce estimates of connectivity for KAZA, including evaluations of proposed movement corridors, suggestions of additional corridors or high-value connectivity areas, etc
- Writes one-to-two publishable papers based on the results above
- Presents the above results in internal meetings and external fora
- Performs other duties as assigned
- Graduate degree in movement ecology, wildlife ecology, or related field; PhD preferred
- Strong background in and experience with statistical methods, including hierarchical Bayesian regression, path selection models, step selection models, resource selection models, GIS, remote sensing, and data from satellite track collars
- Ability to work independently with big data sets and sophisticated data manipulation and analysis
- Familiarity with ArcGIS and the R statistical computing package, with preference for specialized packages such as Circuitscape, stan, or similar
- Experience working in southern African wildlife conservation is preferred
Submit cover letter and resume through our Careers Page, Requisition #18039.
Due to the high volume of applications we are not able to respond to inquiries via phone