Tenure Track: Assistant Professor – Artificial Intelligence in Soil and Crop Sciences

Major Duties and Responsibilities

• Develop a highly impactful, extramurally funded research program integrating artificial intelligence into soil and crop sciences.
• Leverage and integrate varied relevant data (including agronomic, environmental, economic, genomic, nutrition, pest and disease, phenotypic, physiological, management, microbiome, soil, weather, and water) and applications and technologies (such as precision soil and water management, decision-support tools, precision human nutrition, remote sensing, robotics, sensors and variable-rate applications).
• Apply artificial intelligence, machine learning, data analytics, or related computational approaches to soil, crop, environmental, or biological systems.
• Work closely with agronomists, computer scientists, crop physiologists, data scientists, engineers, genomics and genetics researchers, plant breeders, soil scientists, and water researchers in Texas A&M AgriLife Research and the Texas A&M AgriLife Extension Service, both on and off-campus.
• Collaborate with scientists and stakeholders in the region, nationally, and internationally.
• Develop and teach two courses in the Department of Soil and Crop Sciences:
• An introductory undergraduate course on artificial intelligence and its applications in agriculture and environmental sciences, emphasizing Large Language Models and their integration into chatbots and virtual consultants.
• A stacked undergraduate/graduate course focusing on precision agriculture, including topics like agentic AI for autonomous crop and pest management decision-making, foundation and multimodal models, human-robot collaboration for field operations, causal machine learning for interpretable agronomic and ecological modeling, digital twins for real-time crop system simulation and scenario planning, and reinforcement learning for management of cropping systems.
• Provide substantial leadership in developing a new certificate program in digital agriculture and AI applications in soil and crop sciences.
• Advise and mentor undergraduate and graduate students, postdoctoral scientists, and research technicians.
• Publish regularly in peer-reviewed journals appropriate to the discipline.
• Participate in outreach and service activities related to the position.

Required Qualifications

• Ph.D. or equivalent doctoral degree in environmental science, plant or crop science, agronomy, soil science, computer science, bioinformatics, mathematics, statistics, remote sensing, agriculture, biosystems engineering, electrical engineering, or related disciplines.
• Candidates who have completed all Ph.D. requirements except the dissertation (ABD) will be considered provided they demonstrate clear progress toward completion prior to the position start date.
• Strong knowledge and experience in both artificial intelligence as well as agricultural, soil or environmental data.

Desired Qualifications

• Experience working with crops, field-based research, handling large datasets, interdisciplinary collaboration, sensing technologies, and grant writing.
• Excellent oral and written communication skills.
• A good track record of publishing in peer-reviewed journals.
• Teaching experience.

Salary will be commensurable with qualifications and experience. Applications will only be accepted online at https://apply.interfolio.com/189790. Applicants must upload a cover letter (2 pages), curriculum vitae, a list of three referees and their contact information; and a personal statement of their plans for research, teaching, and service (3 pages total). Please clearly indicate in the research and teaching sections a vision for how AI will impact the practice of science and teaching and learning.

To be given full consideration, please submit applications by November 18, 2026. The position will remain open until a suitable candidate is identified.

The anticipated start date is August 16, 2027.

Equal Employment Opportunity Statement: Equal Opportunity/Veterans/Disability Employer.