UC Davis's Department of Wildlife, Fish, & Conservation Biology is lookingfor a Quantitative Wildlife Ecology Postdoctoral Researcher to analyze data from Wildlife Insights, the camera trap-based biodiversity monitoring platform.
Applicants should have a background in Ecology, demonstrated proficiency with R, and an interest in camera trap data. Ideally, this person will also have experience working with hierarchical Bayesian models to analyze wildlife occurrence or abundance data.
Quantitative Wildlife Ecology Postdoctoral Researcher in the Department of Wildlife, Fish, & Conservation Biology
University of California, Davis
Application review begin date: July 31, 2020 (applications will be accepted until position is filled)
Start date is flexible, but expected sometime in the Fall of 2020 or early Winter 2021.
We are seeking a Postdoctoral Researcher with expertise in quantitative ecology, wildlife ecology, global change biology, and/or conservation biology to be jointly advised by Daniel Karp and Rahel Sollmann in the Department of Wildlife, Fish, and Conservation Biology at the University of California, Davis. The appointment will be for one-year, with the possibility of extension based on funding availability and performance.
The postdoctoral researcher will join a collaborative and interdisciplinary team of faculty and conservation practitioners focused on analyzing ‘big data’ to explore regional-to-global trends in wildlife occupancy across space and time. Specifically, the postdoc will be charged with analyzing data and producing analytics for ‘Wildlife Insights’ (https://www.wildlifeinsights.org/), an open-source platform developed by Conservation International and others to share and analyze wildlife data worldwide. Though based at UC Davis, the postdoc will work closely with the Wildlife Insights science advisory board (https://www.wildlifeinsights.org/meet-the-team), especially collaborators at Conservation International (Jorge Ahumada & Eric Fegraus).
In the midst of the ongoing biodiversity crisis, monitoring changes in wildlife populations, identifying novel threats, and evaluating conservation interventions will require reliable, contemporary data on wildlife occurrences and distributions. Scientists and conservation practitioners often use camera traps to monitor wildlife; however, no platform currently exists to share and analyze the vast numbers of wildlife photos collected globally each year. Wildlife Insights was developed to fill this need, harnessing the power of the data revolution to integrate cutting-edge technology and science to develop a global monitoring system for wildlife.
The project postdoc, with advice and mentorship from Karp, Sollmann, and the Wildlife Insights science team, will be responsible for analyzing data from Wildlife Insights to explore the impacts of global change on wildlife occurrences and/or distributions. The postdoc will also produce basic analytics for the Wildlife Insights platform to allow data contributors and other users to better explore and/or visualize their own data. Specific questions and approaches will be developed through an exchange of ideas between the postdoc, Karp, Sollmann, and the Wildlife Insights team; however, we envision community occupancy modeling as playing a central role in analyses. The postdoc will also be responsible for (1) coordinating monthly project meetings, (2) data management, and (3) preparation and submission of one academic manuscript.
Salary and benefits are consistent with UC Davis policy and applicant experience. See link for current salary scale: https://grad.ucdavis.edu/sites/default/files/upload/files/facstaff/salary_19- 20_march_1_2020.pdf
• A Ph.D. in Ecology or a related field.
• Very strong quantitative skills and demonstrated proficiency with R.
• Evidence of commitment to diversity and inclusion in science.
• Strong interpersonal and communication skills and an ability to work both independently and collaboratively with researchers and practitioners from different backgrounds.
• Experience designing, planning, and executing research projects.
• Demonstrated ability to follow through on project deliverables and communicate findings in high quality peer-reviewed journals.
• Strong attention to detail, evidenced by prior research.
The following qualification are preferred but not required:
• Prior experience working with hierarchical Bayesian models to analyze wildlife occurrence or abundance data (i.e., occupancy or N-mixture models).
• Prior experience developing web-based analytics or decision-support tools.
• Prior experience managing large projects.
• Demonstrated ability and/or desire to integrate results across interdisciplinary teams.
Please apply by preparing:
(1) your CV inclusive of publications, awards, and research experience,
(2) a cover letter discussing your qualifications, research interests, quantitative skills, and motivations for this position,
(3) a 1-2 paragraph summary about your commitment to and/or experience with furthering diversity in the sciences, and
(4) contact information for 3 references.
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