Fully Funded PhD in AI-Enabled Modeling of Agricultural Nitrogen Cycling and Greenhouse Gas Emissions North Carolina State University in United States

North Carolina State University is advertising a fully funded PhD position in the Soil Science Program focused on AI-enabled modeling of agricultural nitrogen cycling and greenhouse gas emissions. The project is part of a multi-institutional collaboration aimed at improving predictions of nitrogen use efficiency, N2O emissions, and nitrogen losses in agricultural systems.

The research emphasis includes process-based/biogeochemical models, AI-enabled agroecosystem modeling, model-data fusion, uncertainty quantification, and integration of high-frequency field measurements, soil microbiome data, and environmental datasets. This is a strong fit for students interested in environmental science, agriculture, soil science, earth system science, computer science, and statistics.

Desired preparation includes programming experience in Python, R, Julia, Fortran, C++, or similar languages, plus experience with ML/AI frameworks, statistical inference, and ecosystem/biogeochemical modeling. The post says applicants should have a BS or MS in earth system science, environmental/soil science, data science, computer science, engineering, or a related field.

The supervisor named in the linked faculty page is Debjani Sihi, Assistant Professor at North Carolina State University. Her research program focuses on the plant-soil-microbe-atmosphere continuum, integrating field and laboratory data with machine learning and process-based models, especially for soil carbon and nutrient cycles and greenhouse gas emissions.

To apply, prospective students should email an academic CV and a brief research interest statement to [email protected]. The position is expected to start in Fall 2026 or Spring 2027.