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  • Postdoctoral Associate: riparian biodiversity monitoring in Southern California


    Connor Wood
    • Employer: Cornell Lab of Ornithology
      Location: Ithaca, NY
      Country: United States
      Last Date to Apply: 08/01/2023
      Open Until Filled: Yes

    College Description:  

    The College of Agriculture and Life Sciences at Cornell University embraces diversity and seeks candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We strongly encourage individuals from underrepresented and/or marginalized identities to apply. The Lab of Ornithology's K. Lisa Yang Center for Conservation Bioacoustics, where this position is based, is an inclusive community and welcomes anyone who has an interest in bioacoustics.

    The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and home to Cornell University's second-largest population of students, faculty, and staff. We work across disciplines to tackle the challenges of our time through world-renowned research, education, and outreach. The questions we probe and the answers we seek focus on three overlapping concerns: natural and human systems; food, energy, and environmental resources; and social, physical, and economic well-being. CALS is fundamentally invested in improving the lives of people, their environments, and their communities both in New York state and around the world.

     

    About Us:

    The Cornell Lab is a global leader in ornithological research & conservation and is currently home to a vibrant community of several dozen postdoctoral associates working across all programs. We strive to provide a supportive and collaborative environment for this community that fosters personal growth and career advancement. Within the Lab, the Yang Center (https://bioacoustics.cornell.edu) is defined by its application of bioacoustic techniques to biodiversity conservation. Ecological research, hardware and software engineering, and global capacity building are the Yang Center's pillars of bioacoustic innovation.

    The incumbent will join a lab group in the Yang Center run by Dr. Connor Wood (connormwood.com) to develop a riparian biodiversity monitoring program in Southern California. This is one of two postdoctoral associate openings in this lab; applicants interested in both positions will need to apply separately to each.

     

    Position Function

    Changing fire regimes in dry forest ecosystems in western North America are precipitating potentially massive losses in forest cover. In the mountains of Southern California – and in other arid ecosystems – biodiversity is concentrated in riparian corridors, so fires affecting these areas can have significant conservation implications. However, concentrating post-fire restoration in riparian areas can lead to significant returns. By combining passive acoustic surveys, the machine learning algorithm BirdNET (https://birdnet.cornell.edu), which generates avian diversity data from the audio  (>100 species in the focal landscape), and single- and multi-species occupancy models, the incumbent will address urgent conservation challenges in regional and potentially global biodiversity hotspots. Core objectives of this project include: (1) the implementation of a passive acoustic survey effort to assess the effects of fire and efficacy of restoration in the Transverse Range of Southern California, and (2) using field data and simulations to develop a scalable and transferable monitoring program that could be implemented at broad spatial scales. 

    The project scope provides an opportunity to make direct contributions to conservation and basic ecology. We will collaborate with federal agency biologists and managers (U.S. Forest Service), and academic researchers specializing in ecology, statistics, and computer science. Pending additional funding, the project may be expanded to build upon existing relationships with international NGOs such that the scope of the project entails generalized survey design for arid ecosystems. 

    In addition to working with external partners, the postdoctoral associate will be working closely with scientists in the Yang Center and other programs at the Lab. We encourage postdoctoral associates to explore related research questions and collaborate on projects conducted in the Lab and with partners. 

    This position is a one year-appointment, with a second-year extension with successful performance. Further extension is contingent upon funding. 

     

    Anticipated Division of Time

    Expected outcomes of this work are the submission of two manuscripts to high-impact peer-reviewed journals and coordination with agency partners to directly apply results to conservation in Southern California – and potentially multiple areas in Africa. At least one field season (~3 months in the Angeles National Forest) is required; during the field season, housing, a field vehicle, and additional field staff are all funded. 

    • Develop and conduct avian biodiversity research to meet project goals. Analyze research findings. Apply results to conservation in the Sierra Nevada ecosystem. (60%)
    • Present results at professional meetings, conferences, and popular seminars. Prepare two manuscripts for high impact peer reviewed journals and other research products, including reports and relevant information to partners. (25%)
    • Engaging with partners and possible funders. Participate in career and professional development opportunities. (10%)
    • Engage in ongoing academic and intellectual life at the Lab of Ornithology and Cornell University. (5%)

     

    Supervision Exercised

    The incumbent will be expected to meet regularly with project collaborators (within the Yang Center, at other universities, and in government agencies). In addition, there are opportunities for the incumbent to mentor undergraduate students and possibly contribute to informal mentoring graduate students, but neither activity is expected or required.

     

    Term of position:

    This is a full-time (100% FTE) position and will be located in Ithaca, New York. Local personnel will have the flexibility to work on a hybrid schedule with opportunities to work on-site and from home. Fully remote work will be considered on a case-by-case basis. This is a one-year appointment with possible extension depending on available work, funding and performance.

    Ideal start date is Fall 2023, but applicants available to start as late as Fall 2024 will be considered.

     

    Qualifications

    • Required: A Ph.D. in biological or ecological sciences or statistics.
    • Required: Writing skills and a strong publication record for the professional stage of the applicant 
    • Required: Experience conducting field research; experience conducting passive acoustic surveys is preferred but not required.
    • Preferred: Quantitative skills and experience with terrestrial population modeling, particularly in an occupancy framework. 
    • Preferred: Experience conducting simulation-based power analyses
    • Other beneficial qualifications include: GIS skills, field experience with birds, familiarity with Bayesian statistics, experience working with large acoustic datasets, experience analyzing remotely sensed data, familiarity with machine learning tools, and familiarity with the ecology of Southern California, riparian systems, or arid ecosystems. 

    Writing skills and a strong publication record for the professional stage of the applicant are also valuable. 

     

    Salary and Benefits: 

    Salary range is commensurate with experience, from $56,484 to $64,000 per year and includes benefits. 

     

    Application Instructions: 

    Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/25149. 

    Qualified candidates should submit a short cover letter, curriculum vitae, contact information for three references, and a statement of contribution to diversity, equity, and inclusion via the website. 

    Applications will be reviewed as received, continuing until a suitable applicant is identified. 




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