Up to 30% off — ends 2 Aug
ONLY00h00m00s
Up to 30% off — ends 2 Aug
ONLY00h00m00s
Virginia Tech
4 days ago
Fully Funded PhD in Agroecosystem Modeling, AI, and Sustainable Agriculture at Virginia Tech Virginia Tech in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Sep 1, 2026
Country
United States
University
Virginia Tech

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About this position
Virginia Tech’s Agroecosystem Modeling Lab is recruiting a highly motivated PhD student for a fully funded USDA-NIFA research project starting in Spring 2027.
The project focuses on agricultural diversification practices, especially cover cropping and crop rotation, and their effects on crop yield, soil health, and soil biogeochemical cycling.
Research methods include meta-analysis, process-based agroecosystem modeling (such as DSSAT, APSIM, and DNDC), artificial intelligence, and large geospatial data analysis. This is a strong fit for students interested in agriculture, agroecology, agronomy, soil science, environmental science, remote sensing, data science, and computational modeling.
Ideal applicants should hold an MSc in agroecology, agronomy, soil science, hydrology, remote sensing, or a related field. Experience with crop or ecosystem models is preferred, and programming skills in Python, R, MATLAB, or C++ are expected. Backgrounds in AI, high-performance computing, or data assimilation are a plus.
The position is fully funded and includes tuition, stipend, and benefits. The application deadline is September 1, 2026.
Interested candidates should contact Dr. Yongfa You by email before applying and include a brief research statement, CV, academic transcripts, and three references.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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