Research Associate: Statistical Scientist

Details

Posted: Unknown

Location:

Salary:

Summary:

Summary here.

Details

Posted: 15-Mar-26

Location: Ithaca, New York

Type: Full-time

Categories:

Academic/Faculty

Internal Number: 3-104610

Research Associate: Statistical Scientist

The Cornell Lab of Ornithology is the world's leading resource for conservation, research, education, and citizen science focused on birds. The Lab is a unit within Cornell's College of Agriculture and Life Sciences, where full-time faculty and other renowned professionals direct twelve world-class, mission-driven programs. The Center for Avian Population Studies (CAPS) is one of the major programmatic units at the Lab, collecting and disseminating biodiversity data to enhance the information and decision-making tools available to conservationists and scientific researchers. We achieve this by producing scientific, computational, and big data resources that transform how we understand and protect the world around us.

The Cornell Lab is home to a vibrant community of several research associates working across all twelve programs. We strive to provide a supportive and collaborative environment for this community that fosters personal growth and career advancement. The Lab is an inclusive community, and we recognize that diverse, inclusive communities create more innovative and impactful work to address global challenges and benefit humanity and nature. The Cornell Lab is committed to fostering and sustaining a healthy workplace that values diverse and inclusive perspectives and backgrounds and supports growth and advancement opportunities. The Lab believes that every team member enriches our diversity by exposing us to a broad range of ways to understand and engage with the world, identify challenges, and discover, design, and deliver solutions.

Position Function

The goal of the eBird Status and Trends (S&T) project is to use the information collected by the global participatory science project, eBird, to become the go-to source for publicly available high-quality, high-resolution visualizations, data products, and tools for describing where bird populations occur and how they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling for the biases inherent in species observations collected by volunteers. The workflows generate estimates of species' distributions and abundance, measure how they change over time, and identify the features of the environment associated with populations. Leveraging the broad coverage and fine scale of eBird, these estimates are generated with high resolution across global extents making it possible to address a wide variety of important ecological and conservation applications.

We are seeking a Statistical Scientist to join the Status and Trends (S&T) research team at the Center for Avian Population Studies (CAPS). The desired candidate is an individual excited to address the modeling challenges necessary to develop novel ecological insights and information, data products, and tools. The focus of this position is to develop methods to disentangle dynamic, multiscale ecological signals from large, heterogenous observational data. This work lies at the interface of statistics, machine learning/AI, ecology, and conservation and spans a range of activities from exploratory analysis, visualization, and discovery to prediction, validation, quantification of uncertainty, and inference.

The Statistical Scientist will join a highly collaborative research team to accelerate and extend ongoing research efforts (including DL-based joint species distribution modeling and causal machine learning) and lead methods development to address novel challenges. This position will also collaborate closely with the CAPS scientists to apply research results to advance scientific and conservation objectives.

Anticipated Division of Time

Research and Methods Development (50%)

• Advance existing S&T analyses, production workflows, and data products for transforming participatory science observations into high-resolution estimates of species distributions and trends.
• Work towards/take a leading role developing and adapting emerging approaches for priority applications.
• Publish methodological findings in peer-reviewed statistics or computer science journals and conferences and engage with the broader quantitative and ecological research communities.

Research Applications (30%)

• Partner with the CAPS ecologists and conservation scientists, and external collaborators to advance applications for biodiversity conservation planning and decision-making.
• Collaborate with the production/data engineering team to develop, scale, and deploy analyses for applications and to generate data products.

Mentoring and capacity building (15%)

• Foster the development of a cohesive interdisciplinary data science team within the Center, aligning team goals with the Lab's strategic vision.
• Mentor undergraduate and graduate students contributing to Center projects.
• Supervise postdoctoral fellows, depending on experience.
• Actively participate in lab activities, including team meetings, seminars, and project discussions.

Contributing to activities at Cornell and the Lab of Ornithology (5%)

• Contribute to projects at other Centers within the Lab and participate in interdisciplinary collaborations.
• Engage with campus activities, including seminars, talks, and project meetings.
• Collaborate with the Advancement & Development (Philanthropic-focused) and Communication programs at the Lab as needed.

Term of position

This is a one-year appointment renewable contingent upon satisfactory performance, available work and funding.

Requirements

• Ph.D. in statistics, computer science, or a related field
• Ability to develop, adapt, and apply quantitative methods to answer ecological questions or hypotheses.
• A strong record of conducting independent research and scholarly activities, including publication in peer-reviewed statistics or computer science journals or conferences and experience presenting at scientific conferences.
• Excellent written and verbal communication skills, with the ability to translate complex methodologies into actionable insights for technical and non-technical audiences.
• Proficiency in R & Python for working with the project codebase.

Desired qualifications

• Expertise with spatial, temporal, or spatiotemporal modeling, process-informed spatiotemporal models, causal inference, AI/ML/DL, causal ML, explainable ML, AI/ML/DL, and other relevant analytical skills.
• Experience designing, implementing, testing, and validating statistical learning models for analyzing large and complex environmental or spatiotemporal datasets.
• Experience addressing modeling challenges that commonly arise analyzing ecological &/or observational data such as bias correction, uncertainty quantification, and data integration across a range of inferential objectives, from prediction to statistical testing.
• Proven ability to conduct collaborative research with interdisciplinary teams, from conception to completion.
• Ability to manage multiple projects and priorities in a collaborative, fast-paced research environment.
• Experience mentoring postdoctoral fellows, graduate and undergraduate students.
• Experience in ornithology is a bonus but not required.

Supervision Exercised

The Statistical Scientist will be advised by Dr. Daniel Fink, Statistician and Senior Research Associate in the Center for Avian Population Studies.

Formal supervision of postdoctoral associates within the Cornell Lab.

Training of staff, undergraduates, graduate students, postdocs, and visiting scholars.

Pay Range:

Refer to Posting Language

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:

Notice to Applicants:

EEO Statement:

Cornell welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world-class education and career opportunities, to further the founding principle of "... any person ... any study." No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy-related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual's genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.

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2026-03-13