Senior Research Associate

MSU Jobs • Pearl River, MS

1d

About The Position

Coastal Research and Extension Center, South MS Branch Experiment Station is recruiting a time-limited Senior Research Associate to support specialty crop research with an emphasis on AI and computer vision–driven quantity and quality analysis in specialty crop systems. The successful candidate will lead research activities focused on the development, analysis, and deployment of advanced computer vision and artificial intelligence models for digital agriculture applications, including plant phenotyping, yield estimation, quality assessment, and crop health monitoring. This work will involve designing end-to-end image- and sensor-based data pipelines; acquiring and curating datasets from field and greenhouse environments; developing and validating perception and learning models; and translating quantitative model outputs into agriculturally meaningful metrics that support specialty crop research and decision-making. The candidate will collaborate closely with faculty, research staff, and students to integrate AI-enabled workflows into experimental studies, contribute to grant proposals and peer-reviewed publications, and enhance the Center’s capacity for data-driven agricultural innovation. The position will be based in Poplarville, MS. Mississippi State University’s Coastal Research and Extension Center in support of its South MS Branch Experiment Station (CREC-SMBES) is seeking time-limited Senior Research Associate to support specialty crop research with an emphasis on AI and computer vision–driven quantity and quality analysis in specialty crop systems. The position will be based in Poplarville, MS.

Requirements

• A Master's Degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field is required for this position. The successful candidate must have a minimum of six (6) years of relevant or equivalent research experience.
• A Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field. The successful candidate must have a minimum of three (3) years of relevant postdoctoral or equivalent research experience
• Applicants must possess the skills required to organize and manage assigned duties, including:
• Strong analytical and problem-solving skills related to computer vision and AI model development.
• Excellent written and oral communication skills, including the ability to contribute to scientific publications and grant proposals.
• Ability to work independently as well as collaboratively within interdisciplinary research teams.
• Strong organizational skills with the ability to manage multiple research tasks and timelines concurrently.

Nice To Haves

• Applicants with prior knowledge and experience in digital agriculture, computer vision, machine learning, sensing technologies, and image-based analysis for agricultural or biological systems are particularly encouraged to apply.
• Experience with multimodal sensing, field or greenhouse data collection, and externally funded research projects is highly desirable.

Responsibilities

• Oversee day-to-day operations of digital agriculture and perform data collection in fields across different seasons and environmental conditions, supporting specialty crop systems in field and greenhouse environments.
• Develop and optimize computer vision, machine learning, and AI workflows for image- and sensor-based analysis of quantity and quality, including plant phenotyping, yield estimation, and crop health assessment.
• Establish and maintain data acquisition and analysis pipelines, including imaging protocols, sensor integration, data curation, model training, validation, and performance evaluation.
• Engage with internal and external university and federal partners for other collaborative research projects, including grant proposal development and manuscript preparation.
• Participate in conferences, workshops, and professional development activities to remain current with emerging technologies in digital agriculture, AI, and computer vision.
• Other duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree