Fully Funded PhD Positions in AI for Agriculture at New Mexico State University, USA – Spring or Fall 2027

Overview

The Niu Lab within the Department of Computer Science at New Mexico State University (NMSU) is offering multiple fully funded PhD positions starting in Spring or Fall 2027. Supervised by Dr. Haoyu Niu, the research program operates in an interdisciplinary environment connecting advanced computational technologies with practical agricultural challenges.

Benefits

Stipend to support graduate studies and living expenses
Tuition coverage
Health insurance
Conference travel support

Eligibility

Hold a Bachelor of Science or Master of Science degree in Computer Science, Computer Engineering, Electrical Engineering, Electronic Engineering, Mechanical Engineering, Agricultural Engineering, or a closely related field.
Demonstrate an academic background or strong research interest in artificial intelligence, machine learning, deep learning, reinforcement learning, computer vision, multimodal sensing, robotics, autonomous systems, unmanned aerial or ground vehicles, digital twins, or agricultural systems simulation.
Proficiency in C++ or Python, with experience in ROS or ROS 2 considered desirable.
Willingness to conduct agricultural field experiments.
Strong written and oral communication skills alongside the ability to work effectively in an interdisciplinary team.

How to Apply

Applicants must submit an updated curriculum vitae, academic transcripts, and relevant work samples (such as publications, project reports, or a portfolio) directly by email to Dr. Haoyu Niu at [email protected]. The email subject line must strictly follow the format: “Your Name_PhD Application”. Shortlisted candidates will be invited to a virtual interview.

Deadline

Applications are reviewed on a rolling basis until all positions are filled.

Overview

Eligibility

Hold a Bachelor of Science or Master of Science degree in Computer Science, Computer Engineering, Electrical Engineering, Electronic Engineering, Mechanical Engineering, Agricultural Engineering, or a closely related field.

Demonstrate an academic background or strong research interest in artificial intelligence, machine learning, deep learning, reinforcement learning, computer vision, multimodal sensing, robotics, autonomous systems, unmanned aerial or ground vehicles, digital twins, or agricultural systems simulation.

Proficiency in C++ or Python, with experience in ROS or ROS 2 considered desirable.

Willingness to conduct agricultural field experiments.

Strong written and oral communication skills alongside the ability to work effectively in an interdisciplinary team.

How to Apply