Postdoctoral Associate – Freshwater Nitrous Oxide Modeling

The Cary Institute of Ecosystem Studies invites applications for a postdoctoral associate in freshwater biogeochemistry and machine learning.

The postdoc will collaborate on an NSF-funded project developing a knowledge-guided machine learning model to quantify global riverine nitrous oxide (N2O) emissions.

The project combines process-based modeling with machine learning, and involves compiling and synthesizing global databases of riverine N2O measurements alongside large-scale geocomputation to upscale results across the global river network.

The postdoc will have the opportunity to build interdisciplinary expertise spanning freshwater biogeochemistry, geospatial data science, and machine learning, and to contribute to research relevant to international climate assessments.

Depending on interest and opportunity, there may be scope for the postdoc to engage in limited field-based research on riverine N2O dynamics, complementary to the core project.

Funding for the position is secured for 2 years.

The initial appointment is for one year, with possibility of extension based on performance.

The anticipated start date can be as early as September 2026, with flexibility.

The position is based at Cary Institute in the beautiful Hudson Valley of New York, a short way north of New York City.

The position may have locational flexibility for exceptional candidates.

Cary Institute is home to a diverse, vibrant, and supportive community of colleagues.

Questions about the position and project may be directed to Dr.

Taylor Maavara at Cary Institute.

Essential responsibilities

• Design, plan, and execute scientific research in collaboration with the PI.
• Compile, harmonize, and synthesize a global database of riverine N2O measurements and predictor variables from published and contributed sources.
• Develop and calibrate a knowledge-guided machine learning framework and apply it via large-scale geocomputation across the global river network.
• Present research findings in peer-reviewed papers, at scientific meetings, and in other forums.

Applicants should have expertise in freshwater or riverine biogeochemistry, particularly nitrogen cycling; strong quantitative skills, including experience with process-based modeling and/or machine learning methods; experience handling and synthesizing large, heterogenous environmental datasets; and familiarity with geospatial data science and large-scale geocomputation. A strong record of publishing peer-reviewed research is expected. Applicants should be self-motivated and comfortable working both independently and in close collaboration with the PI. The successful applicant must have completed a PhD in a relevant field before the start date of this position.

Working conditions

The work is primarily office-based.

Occasional travel for meetings is required.

Cary Institute operates on a 35 hour work week.

Closing date

Review of applications will begin July 27, 2026 and continue until the position is filled.

To apply

Visit our website at https://www.caryinstitute.org/... and complete our online job application.

Submit a single file containing a brief cover letter, names and contact information for three professional references, and a curriculum vitae.

The Cary Institute is an Equal Employment Opportunity (EEO) employer.

It is the policy of the Institute to provide equal employment opportunities to all qualified applicants without regard to rate, color, religion, sex, sexual orientation, gender identity, national origin, age, familial status, protected veteran or disabled status, or genetic information.