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

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

Soil and Crop Sciences

Location

College Station

Open Date

8/26/2026

Position ID

187745

Description

Position Description: The Department of Soil and Crop Sciences in the College of Agriculture and Life Sciences at Texas A&M University in College Station, TX, seeks outstanding applicants for a tenure-track Assistant Professor faculty position in Artificial Intelligence in Soil and Crop Sciences. This is a 9-month, full-time, tenure-track faculty position with research, teaching, outreach, and service responsibilities. This position is part of a four-position cluster hire in AI in Agriculture across the College of Agriculture and Life Sciences to develop an undergraduate minor in AI-Enabled Agricultural Systems and build research capacity in this area. The anticipated start date is August 16, 2027.

Major Duties and Responsibilities: The successful applicant will be responsible for developing a highly impactful, extramurally funded research program integrating artificial intelligence into soil and crop sciences. Their work would use artificial intelligence to improve knowledge and outcomes by leveraging and integrating varied relevant data (which may include agronomic, environmental, economic, genomic, nutrition, pest and disease, phenotypic, physiological, management, microbiome, soil, weather, and water), as well as applications and technologies (which may include precision soil and water management, decision-support tools, precision human nutrition, remote sensing, robotics, sensors and variable-rate applications). The successful applicant must demonstrate strong expertise in artificial intelligence, machine learning, data analytics, or related computational approaches, along with experience in applying these tools to soil, crop, environmental, or biological systems.

The individual will 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. Interdisciplinary collaborations with scientists and stakeholders in the region, nationally, and internationally is expected.

The individual will develop and teach two courses in the Department of Soil and Crop Sciences. One course is expected to be an introductory undergraduate course on artificial intelligence and its applications in agriculture and environmental sciences. Emphasis will be given to Large Language Models and their integration into chatbots and virtual consultants. The second course is expected to be a stacked undergraduate/graduate course with a focus on precision agriculture. One or both of these courses should include topics such as 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; or similar topics as they emerge. The individual will be expected to provide substantial leadership in developing a new certificate program in digital agriculture and AI applications in soil and crop sciences.

The individual will advise and mentor undergraduate and graduate students, postdoctoral scientists, and research technicians. They, along with their mentees, will be expected to publish regularly in peer-reviewed journals appropriate to the discipline. They will participate in outreach and service activities related to the position.

Distribution of Effort: 60% research, 30% teaching, and 10% outreach and service

Qualifications

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 are required.

Desired Qualifications: Experience working with crops, field-based research, handling large datasets, interdisciplinary collaboration, sensing technologies and grant writing is desired. Additional qualifications include excellent oral and written communication skills, a good track record of publishing in peer-review journals, and teaching experience.

Salary will be commensurable with qualifications and experience.

Application Instructions

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.

For fruther information, please contact the Search Committee Chair, Dr. Seth Murray at seth.murray@ag.tamu.edu

Application Process

This institution is using Interfolios Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.

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Equal Opportunity/Veterans/Disability Employer.

The University is aware that attracting and retaining exceptional faculty often depends on meeting the needs of two careers and therefore has a Dual Career Program.