Postdoctoral Associate in Agricultural Sciences

access to nutritious food and a healthy environment is a fundamental human right. We believe that ensuring a prosperous global future depends on the ability to support local people and communities everywhere. By working in and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here in New York, across the nation, and around the world.

The Cornell Lab of Ornithology is a global leader in ornithological research and biodiversity conservation and hosts a vibrant community of more than thirty postdoctoral associates working across a range of topics and scales. We strive to provide a supportive postdoctoral environment that fosters scientific discovery, collaboration, and professional development. The postdoctoral associate will be affiliated with the Center for Avian Population Studies (CAPS, https://www.birds.cornell.edu/home/center-for-avian-population-studies/), one of six programmatic units at the Cornell Lab. CAPS is the home of the eBird project, one of the largest sources of avian biodiversity information in the world. The eBird team is a collaborative and innovative group that includes staff with deep expertise in bioinformatics, statistics, and ornithology.

The postdoctoral associate will be advised by Dr. Laurel Symes (symes@cornell.edu), and will also have the opportunity to work closely with colleagues from other programs at the Lab of Ornithology and across Cornell University.

POSITION FUNCTION

With over two billion observations from hundreds of thousands of participants globally, eBird is the world's largest community science initiative for biodiversity monitoring. eBird observations are used to infer relative abundance at scale, key for ecological study and conservation efforts. Audio recordings of bird calls and song, both from cell phones and dedicated recording devices, are also growing in scale, creating the potential to complement, extend, and expand human observations. However, a key challenge is translating imperfect, behaviorally-mediated acoustic observations into estimates of the number of individuals present.

We seek a postdoctoral associate to collaborate with us on developing approaches that translate acoustic observations into calibrated estimates of relative abundance and assessing how those estimates can complement eBird-based monitoring. The specific methodological direction will be shaped jointly, drawing on the successful candidate’s interests and expertise as well as the data and perspectives of collaborating teams. We are particularly interested in approaches applicable to single-channel recordings at broad scales, while recognizing that integrating multielement microphones, acoustic arrays, and other approaches may provide valuable calibration and validation. Together, we will evaluate approaches based on inferential validity, uncertainty, transfer across species, sites, and recording systems, and comparison with independent benchmarks.

POTENTIAL RESEARCH DIRECTIONS

The following examples illustrate potential avenues of research rather than a required work plan. They may be pursued individually or in combination, and we welcome other creative and strategic approaches.

• Statistical or machine-learning approaches that estimate abundance, density, or related population measures from raw audio or acoustic detections. These approaches may use eBird observations or eBird Status products as covariates, priors, or sources of comparison, with careful attention to relationships among the data sources and the need for independent validation.
• Hierarchical models that represent relevant components of the acoustic observation process—such as vocal activity, sound transmission, detection, and classification—and integrate acoustic and eBird data to estimate underlying abundance and associated uncertainty.
• Behavioral approaches that quantify variation in inter-call intervals, call repetition rates, or other vocal characteristics and investigate how that variation affects inference about the number of individuals present.
• Individual vocal discrimination, including long-term recognition of individuals or short-term differentiation among simultaneously or recently vocalizing individuals.
• Single- or multi-channel source-separation approaches, including machine-learning methods, that improve the identification or enumeration of overlapping vocal individuals.
• Array localization, spatially explicit capture-recapture, distance sampling, or other information-rich approaches that can provide calibration and validation data.
• Comparisons that use these independent benchmarks to characterize the identifiability, bias, uncertainty, and transferability of methods intended for broader-scale application to single-channel recordings.

We do not expect any single method to perform equally well across all species, environments, recording systems, or density ranges. We recognize that acoustic-based abundance estimation may ultimately require multiple complementary approaches that address different components of the acoustic observation process and provide different levels of precision across contexts. Identifying where and why different approaches succeed or fail—and determining the level of inference that different data can support—will itself be an important research contribution.

The incumbent will have access to multiple datasets, including passive acoustic data accompanied by strong labels, acoustic data from areas with substantial eBird activity, and the option to collect additional acoustic data if needed. In addition to these core resources, the postdoctoral associate will have access to raw eBird data (> 2 billion observations), the ability to engage with the eBird Status and Trends modeling team, access to high-performance computing resources, and opportunities to collaborate with researchers from other programs at Cornell University. In the proposed approach, we encourage applicants to draw on their demonstrated skills. Please reach out as needed with questions about available training data or other resources required for your proposed approach.

The postdoctoral associate will be a key contributor to envisioning and advancing biodiversity monitoring, particularly the ability to maximize the impact of acoustic data in the eBird monitoring framework. This position will help define the Cornell Lab's long-term research agenda at the intersection of community science, acoustic monitoring, and statistical ecology.

This is a one-year appointment, with extension for an additional year contingent upon available work and performance. This position is funded for 2 years. Additional extensions are possible contingent upon additional funding, work and performance. Funding will be provided for conference participation and other professional development activities.

As part of the training, the postdoctoral associate will gain experience working with researchers from different disciplines and will receive training in proposal writing, collaborative science, and translating research to application.

ANTICIPATED DIVISION OF TIME

Working collaboratively, we will establish a focused and achievable set of research goals for the appointment, tailored to the successful candidate’s interests and expertise. Anticipated outcomes include a framework for benchmarking and validating acoustic estimates of abundance or density; the development and evaluation of one or more promising, scalable approaches; characterization of uncertainty and transferability across relevant species, sites, and recording systems; and reproducible code or analytical workflows. The postdoctoral associate will also lead or contribute substantially to peer-reviewed manuscripts, presentations, and practical recommendations for integrating acoustic information with eBird-based monitoring. The precise balance among these outcomes will be determined jointly as the project develops.

Approximate Distribution of Time

• Engage with teams working with eBird and acoustic data to understand these datastreams and the opportunity space for integration (15%).
• Develop approaches for understanding acoustic observation processes and estimating abundance from acoustic data (40%).
• Prepare and submit manuscripts to peer-reviewed journals. Present results at professional meetings, conferences, and public seminars (30%).
• Engage with colleagues at the Cornell Lab, external 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%).

QUALIFICATIONS

• A Ph.D. in a relevant field (e.g. machine learning, ecology, biological sciences, computer science, statistics, engineering)
• Demonstrated quantitative skills, including proficiency in programming (R and/or Python)
• Demonstrated expertise in one or more relevant areas, with the ability and interest to develop new approaches at the intersection of methods development, acoustic monitoring, and ecology
• Ability to work independently and collaboratively as part of interdisciplinary research teams
• Enthusiasm for enhancing ecological monitoring and supporting conservation decision-making

Preferred Qualifications

• Previous experience with passive acoustic monitoring and/or eBird data
• Strong background in statistical modeling
• Familiarity with ecology and/or ornithology
• Demonstrated ability to publish peer-reviewed research

SUPERVISION EXERCISED

The incumbent will have opportunities to engage in undergraduate mentorship. There are no supervisory responsibilities with this position.

SALARY, REWARDS, AND BENEFITS

CALS hiring rate for this position is $65,000.

The position is based in Ithaca, NY, where personnel will have the flexibility to work on a hybrid schedule (4 days on site) with opportunities to work on-site and from home.

Benefits provided by Cornell include a broad range of comprehensive health care options, generous paid leave provisions: 3 weeks of vacation, 13 holidays (including end of year winter break), paid family leave, and superior retirement contributions. Additionally, Cornell provides access to professional development initiatives, wellness programs, and employee discounts with local and national retail brands.

TO APPLY

Please apply via Academic Jobs Online:

https://academicjobsonline.org/ajo/jobs/32728

Qualified candidates should submit a short cover letter, curriculum vitae, one page statement of proposed research focus and approach, and contact information for three references.

Review of applications will begin four weeks after posting and will continue until a suitable applicant is identified.

Consistent with Cornell’s practice, appointments to academic positions require candidates to disclose relevant information about their prior employment including whether they have been found to have violated institutional or employer policies related to or governing unlawful discrimination and harassment, academic and research misconduct, or financial misconduct.

COLLEGE OF AGRICULTURE AND LIFE SCIENCES

Life. Changing.

Cornell University is an innovative Ivy League and Land-grant university and a great place to work. Our inclusive community of scholars, students, and staff impart an uncommon sense of larger purpose and contribute creative ideas to further the university's mission of teaching, discovery, and engagement.

Cornell’s regional and global presence includes state-wide Cornell Cooperative Extension programs and offices in all counties and boroughs, global partnerships with institutions and communities engaged in life-changing research and education, the medical college’s campuses on the Upper East Side of Manhattan and Doha, Qatar, and the Cornell Tech campus on Roosevelt Island in the heart of New York City.

With a founding principle of “any person, any study,” Cornell is an equal opportunity employer.

PAY RANGE

$62,232.00 - $88,745.00

PAY RANGES

The hiring rate of pay for the successful candidate will be determined considering the following criteria:

• Prior relevant work or industry experience.
• Education level to the extent education is relevant to the position.
• Academic Discipline
• Unique applicable skills.

EMPLOYMENT ASSISTANCE

For general questions about the position or the application process, please contact the Recruiter listed in the job posting or email mycareer@cornell.edu.

If you require an accommodation for a disability in order to complete an employment application or to participate in the recruiting process, you are encouraged to contact Cornell Office of Civil Rights at voice (607) 255-2242, or email at accommodations@cornell.edu.

Applicants that do not have internet access are encouraged to visit your local library, or local Department of Labor. You may also request an appointment to use a dedicated workstation in the Office of Talent Attraction and Recruitment, at the Ithaca campus, by emailing mycareer@cornell.edu.

NOTICE TO APPLICANTS

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This notice contains important information about applying for a position at Cornell as well as some of your rights and responsibilities as an applicant.

EEO STATEMENT

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Cornell University embraces diversity in its workforce and seeks job candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We hire based on merit, and encourage people from historically underrepresented and/or marginalized identities to apply. Consistent with federal law, Cornell engages in affirmative action in employment for qualified protected veterans as defined in the Vietnam Era Veterans’ Readjustment Assistance Act (VEVRAA) and qualified individuals with disabilities under Section 503 of the Rehabilitation Act. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.

2026-09-16