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Virginia Tech

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Fully Funded PhD in AI for Sustainable Agriculture at Virginia Tech Virginia Tech in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD position.

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Country

United States

University

Virginia Tech

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Keywords

Computer Science
Data Science
Environmental Science
Agriculture
Biology
Remote Sensing
Geography
Artificial Intelligence
Earth Science
Sustainable Agriculture
Ecological Modeling
Statistics
ML

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About this position

Fully funded PhD opportunity at Virginia Tech in AI for Sustainable Agriculture, hosted by the Ecosystem Intelligence Lab. The project sits at the intersection of artificial intelligence, machine learning, remote sensing, agroecosystems, and climate-resilient agriculture.

Research themes include AI-driven decision support for sustainable agriculture, satellite remote sensing and machine learning, process-based ecosystem modeling, and agroecosystem dynamics under climate stress. This is a strong fit for students interested in data-driven environmental and agricultural research with quantitative and programming components.

Eligibility highlights: a Bachelor’s or Master’s degree in a relevant field such as Agricultural or Environmental Engineering, Remote Sensing, Ecology, Geography, Computer Science, or Data Science; strong programming and quantitative skills; and a clear interest in machine learning and independent research.

Funding is described as fully funded. The post does not mention a deadline, but notes that interviews for shortlisted candidates are expected between late October and mid-November 2026, and interested candidates should contact the professor soon.

How to apply: send a single PDF containing your CV, academic transcripts, and a brief statement of research interests and experience to Dr. Yanghui Kang at [email protected]. An official graduate program link is also provided for more information.

Funding details

Fully funded PhD position.

What's required

Applicants should have a Bachelor’s or Master’s degree in a relevant field such as Agricultural or Environmental Engineering, Remote Sensing, Ecology, Geography, Computer Science, or Data Science. Strong programming and quantitative skills are required, along with interest in machine learning, agroecosystems, and independent research.

How to apply

Prepare one combined PDF containing your CV, academic transcripts (Bachelor’s and Master’s if applicable), and a brief statement of research interests and experience. Email the materials to Dr. Yanghui Kang at [email protected] and contact the professor soon for consideration.

More information can be found here

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