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Sara Beery

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PhD Students in Computer Vision and Machine Learning for Global Biodiversity Monitoring Massachusetts Institute of Technology in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Dec 1, 2026

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Country

United States

University

Massachusetts Institute of Technology

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Keywords

Computer Science
Ecology
Environmental Science
Biology
Artificial Intelligence
Computer Vision
ML

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About this position

Sara Beery is recruiting PhD students to join the BeeryLab at the Massachusetts Institute of Technology, beginning in Fall 2027. The lab develops computer vision and machine learning methods for biodiversity monitoring at a global scale.

The research sits at the intersection of artificial intelligence, computer vision, ecological observation, and conservation science. Students will contribute to methods and computational tools that help monitor biodiversity across large geographic areas, supporting data-driven understanding of ecosystems and species.

The opportunity is based at MIT and may be pursued through MIT EECS, the MIT-WHOI Joint Program, MIT EAPS, or MIT CEE, depending on the student's research fit. The BeeryLab provides an interdisciplinary environment for applying modern machine learning to challenges in ecology and global biodiversity monitoring.

The advert invites applications for Fall 2027 and directs prospective students to the MIT PhD application process and the BeeryLab research page.

Funding details

Available

What's required

Applicants should apply directly to an MIT PhD program and list Sara Beery as a potential advisor. Relevant routes include MIT EECS, the MIT-WHOI Joint Program, MIT EAPS, or MIT CEE, depending on fit. No additional academic, technical, GPA, or language-test requirements are stated.

How to apply

Submit an application directly to the MIT PhD program by December 1, 2026, listing Sara Beery as a potential advisor. Applicants may also complete the BeeryLab interest survey and should not expect meetings with prospective applicants before formal review.

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United States

Research Interests

Ecology

Artificial Intelligence

Landscape Ecology

Environmental Conservation

Computer Vision