A fully funded PhD position is available in the Department of Agricultural & Biological Engineering at Mississippi State University, USA, for research in the Advanced Plant & Soil Sensing (APSS) Lab led by Dr. Nuwan Wijewardane. The lab focuses on developing and applying advanced sensing technologies, including spectroscopy, for plant and soil sensing, with the goal of contributing to precision agriculture and eco-friendly agricultural practices. Graduate students in the lab are trained in machine learning, spectroscopic sensing, and plant and soil sciences, and are expected to collaborate in multidisciplinary research environments.

The position covers stipends, tuition waivers, and insurance, with an anticipated start date in Summer/Fall 2026. Applicants should have a bachelor’s or master’s degree in Agricultural and Biological Engineering, Biosystems Engineering, Computer Science and Engineering, Mechanical/Electrical Engineering, or a related field, with a minimum GPA of 3.0. Strong English writing and communication skills are required, and non-native English speakers must provide TOEFL (≥79 iBT) or IELTS (≥6.5) scores. Preferred qualifications include experience in data analysis, spectroscopy, sensing, mechatronics, programming (Python or MATLAB), proficiency in machine learning and AI, and a record of scientific publications.

Interested candidates should apply through the provided online form and prepare a cover letter describing research interests, a CV, transcripts, test scores, and a list of three references. Direct emailing is discouraged. Review of applications will begin immediately and continue until the positions are filled. For more details on graduate application procedures, visit the Mississippi State University Graduate School website.

Research in the APSS Lab is at the intersection of agricultural engineering, biological sciences, computer science, and environmental science, with a strong emphasis on developing novel sensors and data-driven solutions for field applications. The lab’s mission is to enhance agricultural productivity through innovative sensing, data analysis, and control techniques for crops, soil, and animals.