Publisher
source

Cornell University

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Postdoctoral Associate in Statistical Integration of eBird and Acoustic Data Cornell University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Funded for 2 years as two consecutive one-year appointments, with possible extensions contingent on funding and performance. Salary is $65,500 and includes benefits. Funding is also provided for conference participation and other professional development activities.

Deadline

Oct 5, 2026

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Country

United States

University

Cornell University

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Keywords

Computer Science
Environmental Science
Biology
Spatial Statistics
Hierarchical Modeling
Bioacoustics
Statistics
ML

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About this position

Postdoctoral Associate at Cornell University (Cornell Lab of Ornithology, College of Agriculture & Life Sciences) in Ithaca, New York, United States.

This postdoctoral position focuses on the statistical integration of eBird and acoustic data for avian biodiversity monitoring, conservation decision-making, and statistical ecology. The successful candidate will work with the Cornell Lab of Ornithology, the Center for Avian Population Studies (CAPS), and collaborators across Cornell, including the Cornell K. Lisa Yang Center for Conservation Bioacoustics and the Macaulay Library of Natural Sound.

Research directions may include integrated modeling, uncertainty propagation, joint occupancy estimation, calibration of detection probabilities, converting acoustic recordings into eBird-compatible checklists, adaptive sampling, and correcting observer-, sensor-, and habitat-specific detection bias. The role offers access to large datasets, including passive acoustic recordings, millions of hours of audio, and raw eBird data, plus high-performance computing resources.

Eligibility requires a Ph.D. in a relevant field such as statistics, ecology, biological sciences, computer science, or machine learning. Strong quantitative and programming skills in R and/or Python are expected, along with experience in statistical methods, machine learning, and large datasets. Preferred experience includes Bayesian hierarchical modeling, occupancy modeling, joint species distribution models, spatial statistics, passive acoustic monitoring, eBird data, and reproducible research workflows.

The position is funded for 2 years, with a salary of $65,500 plus benefits and support for conference participation and professional development. Applications are reviewed starting 2026-10-05 and continue until filled. Apply through Academic Jobs Online with a cover letter, CV, and three references.

Funding details

Funded for 2 years as two consecutive one-year appointments, with possible extensions contingent on funding and performance. Salary is $65,500 and includes benefits. Funding is also provided for conference participation and other professional development activities.

What's required

A Ph.D. in a relevant field such as statistics, ecology, biological sciences, computer science, or machine learning is required. Applicants should have demonstrated quantitative skills, proficiency in R and/or Python, experience developing statistical methods or machine learning approaches, experience working with large datasets, and the ability to work independently and collaboratively in interdisciplinary teams. Preferred qualifications include Bayesian hierarchical modeling, occupancy modeling, joint species distribution models, integration of multiple data types, spatial statistics, machine learning, passive acoustic monitoring, eBird data, ecology or ornithology familiarity, peer-reviewed publication experience, and reproducible workflows using version control.

How to apply

Apply via Academic Jobs Online. Submit a short cover letter, CV, and contact information for three references through the application website. Applications are reviewed as received starting October 5, 2026 until a suitable applicant is identified.

More information can be found here

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