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Congliang Zhou

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PhD and Masters Positions in Agricultural Robotics and AI in Precision Agriculture at Louisiana State University Louisiana State University in United States

I am recruiting PhD and Master's students in Agricultural Robotics and AI in Precision Agriculture.

Louisiana State University

United States

email-of-the@publisher.com

Feb 1, 2026

Keywords

Computer Science
Machine Learning
Agriculture
Mechanical Engineering
Deep Learning
Remote Sensing
Artificial Intelligence
Computer Vision
Sensor Fusion
Precision Agriculture
Robotics
Autonomous System
Agricultural Robotics

Description

Louisiana State University is offering graduate research assistantship opportunities for highly motivated PhD and Master's students in the field of Agricultural Robotics and AI in Precision Agriculture. The positions are based in the School of Plant, Environmental, and Soil Sciences, located in Baton Rouge, Louisiana, with an anticipated start date in the Summer or Fall semester of 2026. Successful candidates will conduct innovative research in agricultural robotics, AI-driven decision support systems, and computer vision applications for precision agriculture. Responsibilities include designing and implementing autonomous systems and robotic platforms for crop monitoring and management, developing advanced machine learning and deep learning models to address complex challenges in precision agriculture, and integrating remote sensing and sensor fusion techniques with robotic systems for real-time data acquisition and analysis. Students will also have the opportunity to publish findings in high-impact journals, present at leading conferences in robotics, AI, and agricultural technology, and collaborate with industry partners to deliver research-based solutions that support sustainable agriculture. Applicants should have a bachelor's or master's degree in Agricultural Engineering, Computer Engineering, Mechanical Engineering, Geography, Crop Science, or related fields, with a strong emphasis on robotics, artificial intelligence, and computer vision. Required skills include hands-on experience in robotic system design, sensor integration, and automation technologies, proficiency in programming languages such as Python, C++, and ROS, and familiarity with data analysis tools for agricultural applications. Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch) for image processing, and experience with remote sensing, GIS, and spatial analysis for precision agriculture are highly desirable. Strong communication skills and the ability to work in multidisciplinary teams are essential. Graduate assistantship funding is available, though specific details regarding stipend and tuition coverage are not provided. Interested applicants should apply to the graduate programs at Louisiana State University and contact Dr. Congliang Zhou with their CV, research statement, unofficial transcripts, and contact information for three references. The application deadline is February 1, 2026. For more information, visit the LSU Graduate School admissions page.

Funding

Graduate assistantship opportunities are available. The position is likely fully funded, but specific stipend amounts and tuition coverage are not detailed in the announcement.

How to apply

Apply to the graduate programs at Louisiana State University by February 1, 2026. Contact Dr. Congliang Zhou with your CV, research statement, unofficial transcripts, and contact information for three references. Review the application details at the provided LSU Graduate School link.

Requirements

Applicants must have a bachelor's or master's degree in Agricultural Engineering, Computer Engineering, Mechanical Engineering, Geography, Crop Science, or related fields with strong emphasis on robotics, artificial intelligence, and computer vision. Hands-on experience in robotic system design, sensor integration, and automation technologies is required. Proficiency in programming languages such as Python, C++, and ROS, as well as data analysis tools for agricultural applications, is expected. Knowledge of deep learning frameworks like TensorFlow or PyTorch for image processing, and familiarity with remote sensing, GIS, and spatial analysis for precision agriculture are preferred. Strong communication skills and ability to work in multidisciplinary teams are also required.

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