Fully Funded PhD in Agricultural Artificial Intelligence, Computer Vision, and 3D Reconstruction
Fully funded PhD Graduate Research Assistantship
at
Tennessee Tech University
in the
School/College of Agriculture
for research on
agricultural artificial intelligence
,
computer vision
,
root phenotyping
, and
3D reconstruction
.
The project is USDA-NIFA funded and focuses on developing advanced techniques for studying and analyzing
corn roots
using image processing, AI, deep learning, and modern imaging systems. The work includes field and laboratory experiments, collecting and processing root images, building 3D models, analyzing data, preparing scientific papers, and presenting at conferences. Collaboration is mentioned with researchers at Tennessee Tech and the University of Illinois Urbana-Champaign (UIUC).
Research keywords:
agricultural AI, precision agriculture, computer vision, image processing, deep learning, machine learning, photogrammetry, geospatial technologies, agricultural sensing, 3D modeling.
Eligibility highlights:
applicants should hold a master's degree in Agricultural Engineering, Biosystems Engineering, Electrical Engineering, Data Science, or a related field. Experience with Python, OpenCV, and image-processing workflows is required, along with a strong interest in AI, computer vision, and precision agriculture. Preferred experience includes machine learning, deep learning, camera calibration, photogrammetry, 3D modeling, and geospatial technologies.
Funding:
fully funded Graduate Research Assistantship with tuition fee waiver, monthly stipend/salary, and research support.
Application materials:
cover letter, CV, academic transcripts, and contact information for three references. Applications are to be submitted electronically by email to Dr. Abdul Momin at
[email protected]
.
Start date:
preferred Fall 2026.
