LEAP's 2025 Research Experience for Undergraduates (REU) Program

Employer: LEAP-STC (Learning the Earth with Artificial Intelligence + Physics) at Columbia University
Location: New York, NY and/or Boulder, CO
Salary: $700/week stipend
Closing date: Mar 15, 2025

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Discipline: Atmospheric Sciences, Cryosphere Sciences, Geochemistry, Global Environmental Change, Hydrology, Interdisciplinary/Other, Natural Hazards, Near Surface Geophysics, Ocean Science, Social Sciences , Solid Earth Geophysics, Volcanology, Geochemistry, and Petrology, GeoHealth
Career Level: Student / Graduate
Education Level: Bachelors
Job Type: Internship
Relocation Cost: No Relocation
Sector Type: Academia

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Job Details

LEAP’s 2025 Research Experiences for Undergraduates (REU) Program offers summer undergraduate research experiences (SUREs) on synergistic innovations in data science and climate science. The REU Program hosts undergraduate researchers and offers a wide array of enrichment learning and networking opportunities. LEAP is committed to building a vibrant research community at the intersection of climate science, data science, and real-world impact. All students will be supported by a team of researchers and graduate student mentors. We want our students to succeed and learn what it takes to make a larger impact on the world via STEM research. Upon completion of the Program, students may have the opportunity to continue their research or present their findings at academic conferences.

We invite applications from students who will be a rising sophomore, junior, or senior in Fall 2025 at a college/university in the United States. (We are only able to offer admission to U.S. citizens and permanent residents.) We invite all students to apply. Former LEAP REU participants are also welcome to apply.

What are the application requirements?

Online Application
Résumé/CV
Academic transcript (unofficial transcripts are acceptable)
Statement of interest (500 words about your research goals this summer and your future plans)
Letter of recommendation from an academic professor with whom you have studied at your home institution
Please be sure to read each project description carefully before submitting the application. Project descriptions may be found at: https://leap.columbia.edu/wp-content/uploads/2025/02/2025-REU-Project-Descriptions-1.pdf

How do I apply? And what are the deadlines?

The Application is available online.
Applications are due by Sunday, March 15, 2025, 11:59 p.m. (EDT).
Letters of recommendation should be submitted via email to LEAP@columbia.edu by Sunday, March 15, 2025, 11:59 p.m. (EDT).
We anticipate notifying applicants with a decision at the end of March 2025.

Where will the 2025 REU Program be located?
The 2025 REU Program — including enrichment and social activities — will be held at Columbia University’s Morningside Heights campus and Manhattanville Campus; some projects may also be based in Boulder, CO. LEAP’s office is located in the Columbia Engineering Innovation Hub.

How much is the stipend?
The 2025 REU Rrogram offers a competitive stipend of $700 per week for the duration of the program.

Will travel funds be provided?
A travel stipend will be available for eligible students.

Company

Learning the Earth with Artificial Intelligence and Physics (LEAP) is an NSF Science and Technology Center (STC) launched in 2021 with the mission to increase the reliability, utility, and reach of climate projections through the integration of climate and data science. LEAP’s primary research strategy is to improve near-term climate projections by merging physical modeling with machine learning across a continuum from expertise in climate science and climate modeling to cutting-edge machine learning algorithms. The benefits will be significant for both the climate and data sciences communities. Climate scientists and modelers struggle to fully integrate the wealth of existing datasets into their models, while machine learning algorithms have been good at emulating and interpolating but have difficulties extrapolating or predicting extremes. By combining both approaches, LEAP will trigger a significant advancement for data science algorithms applied to physical problems. LEAP will incorporate physics and causal mechanisms into machine learning algorithms for better generalization and extrapolation, while optimally using the wealth of data available to climate science, in order to better predict the future.

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