Luis Avila
1 week ago
PhD Position in Machine Learning, Agriculture, and Geospatial Analytics Mississippi State University in United States
Degree Level
PhD
Field of study
Computer Science
Funding
The position offers a multidisciplinary research environment, strong industry and stakeholder engagement, opportunities for high-impact publications, and training in AI applications in agriculture. Specific funding details such as stipend amount or tuition coverage are not mentioned.
Country
United States
University
Mississippi State University

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About this position
The Weed Science Research Group at Mississippi State University is offering a PhD opportunity focused on the intersection of machine learning, agriculture, and geospatial analytics. The successful candidate will collaborate with Dr. Luis Avila at Mississippi State University and Dr. Muthukumar Bagavathiannan at Texas A&M University. The research will address real-world agricultural challenges using AI-driven solutions, particularly in UAV-based weed detection, classification, and herbicide application optimization.
Applicants should have a background in Agronomy, Crop Science, Agricultural Engineering, Precision Agriculture, or a related field, with strong coding skills in Python and a solid quantitative/statistical foundation. Preferred qualifications include experience with machine learning frameworks, geospatial tools, remote sensing or UAV imagery, and knowledge of crop production or weed science systems.
The position provides a multidisciplinary research environment, strong industry and stakeholder engagement, opportunities for high-impact publications, and advanced training in AI applications for agriculture. The research group is committed to advancing the use of technology in agricultural systems, with a focus on practical, impactful outcomes.
Applications must be submitted through the official application link. Direct messages or emails with application materials will not be considered. This is an excellent opportunity for candidates passionate about applying AI and machine learning to solve agricultural problems and contribute to innovative research in the field.
Funding details
The position offers a multidisciplinary research environment, strong industry and stakeholder engagement, opportunities for high-impact publications, and training in AI applications in agriculture. Specific funding details such as stipend amount or tuition coverage are not mentioned.
What's required
Applicants must have a bachelor's degree in Agronomy, Crop Science, Agricultural Engineering, Precision Agriculture, or a related field. Strong coding skills in Python are required, with R as a plus. Candidates should have a solid quantitative and statistical foundation. Preferred experience includes familiarity with machine learning frameworks, geospatial tools, remote sensing or UAV imagery, and an understanding of crop production or weed science systems.
How to apply
Submit your application through the provided application link. Do not send direct messages or application materials via email or social media. Follow the instructions on the application portal for next steps.
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