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Professor Javad M. Velni at Clemson University is recruiting multiple PhD students for two new NSF- and USDA-funded projects in the field of digital agriculture. The research will focus on developing next-generation autonomous greenhouse platforms and distributed multi-agent field-based agricultural systems. Key research areas include physics-informed modeling, plant-centered sensing, adaptive and reinforcement-learning–based control, digital twins, vision-guided robotic interaction, and decentralized control architectures. The projects aim to optimize crop growth, resource efficiency, and economic performance through advanced robotics and machine learning techniques. Applicants should have a strong background in computational science, especially in control and machine learning. Experience in plant sciences is a plus. Preference is given to candidates with an M.S. degree in Mechanical Engineering or Electrical Engineering and research experience in learning-based control or precision agriculture. The positions are fully funded by NSF and USDA grants, providing an excellent opportunity for students interested in digital agriculture, robotics, and control systems. To apply, qualified candidates should submit a complete CV and academic transcripts in a single PDF to Professor Javad Velni at [email protected]. Only relevant inquiries from qualified candidates will receive a response. For more information, visit Professor Velni's LinkedIn profile .