Post-doc sought to model species occurrence with eBird data
By Team eBirdSeptember 2, 2014
The Information Science Program at the Lab of Ornithology and the Smithsonian Migratory Bird Center are currently seeking a joint Post-doctoral Associate to be based at the Cornell Lab of Ornithology in Ithaca NY. Duties would include: Conduct original research in the field of statistics and machine learning to advance the understanding of species distributions for ecological studies and conservation planning. Successful applicants are expected to develop innovative methods to estimate patterns of species abundance through space and time and utilizing the unique data resources available through the Information Science program. In particular, conducting research using the eBird database, the largest ecological crowdsourced database currently available.
The appointee will promote interdisciplinary dialogue and collaboration, and take a lead role in projects that include:
conducting and collaborating on original research in the area of spatiotemporal analysis and semiparametric regression applied to avian ecology with a broad geographic perspective, publishing in scientific journals, researching and writing proposals, generating maps of species occurrence, and writing white papers to support the group’s research goals;
conception and generation of R software and packages in high performance computing environments;
consulting with other researchers in a collaborative environment including, ecologists, ornithologists, statisticians, computer scientists, application developers, and data base administrators to advise on strategies with the goal of improving data analysis and the efficiency and accuracy of the data collection.
This is a full-time, 1-year initial appointment renewable pending available funding.
PhD in statistics, machine learning or a closely related field.
A track record of independent research
Strong publication record in leading journals including both methodological and applied research.
Proficiency in R including experience in high performance computing environments. Experience publishing packages is desired.
Excellent oral and written communication skills.
Must have a record of successfully meeting schedules and milestones of research projects that involve multiple stages and several participants.
Must have a strong record of enhancing the performance of a multi-disciplinary research team and conducting research that supports the needs and mission of the program.
Interested applicants should submit cover letter, CV and the names and contact information for 3 references.