Bob (Zhiwei) Zeng
1 week ago
Funded MSc & PhD Positions in Digital Twins, Agricultural Machinery, and Precision Agriculture Oklahoma State University in United States
Degree Level
Master's, PhD
Field of study
Agriculture
Funding
The positions are fully funded, including tuition coverage, a competitive stipend, and health insurance.
Deadline
Expired
Country
United States
University
Oklahoma State University

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About this position
The Zeng Lab at Oklahoma State University is recruiting motivated MSc and PhD students for Fall 2026 to join a new research group in the Department of Biosystems & Agricultural Engineering. The lab, led by Associate Professor Bob (Zhiwei) Zeng, focuses on the development of digital twins for next-generation agricultural machinery, with research areas spanning off-road machinery, DEM/CFD/MBD simulation, soil-tool interaction modeling, intelligent sensing and AI integration, and sustainable mechanization systems.
Students will have the opportunity to work at the intersection of agriculture, mechanical engineering, and computational modeling, contributing to the advancement of precision agriculture and sustainable farming technologies. The lab emphasizes close mentorship, intellectual freedom, and rigorous research standards, aiming to develop future leaders in the field.
Funding is fully provided, covering tuition, a competitive stipend, and health insurance. Applicants should have a background in agricultural engineering, mechanical engineering, or related disciplines, and an interest in digital twins, simulation, and intelligent systems. Experience with simulation tools or AI is a plus.
The application deadline is December 28, 2025, for a Fall 2026 start. For more information and application instructions, prospective students should consult the full LinkedIn post or contact the lab directly.
Funding details
The positions are fully funded, including tuition coverage, a competitive stipend, and health insurance.
What's required
Applicants should be self-motivated and research-driven, with a strong interest in machinery systems, digital twins, and precision agriculture. A relevant undergraduate or graduate degree (such as in agricultural engineering, mechanical engineering, or related fields) is expected. Experience or coursework in simulation (DEM, CFD, MBD), soil-tool interaction, intelligent sensing, or AI integration is desirable. No specific GPA, language, or test requirements are mentioned.
How to apply
Read the full post for detailed research areas and application instructions. Interested candidates should reach out to the lab or supervisor directly. Follow the provided LinkedIn post or scan the QR code for more information.
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