Full Time Plant Phenotyping Jobs (NOW HIRING)

Description
The Department of Horticultural Sciences in the College of Agriculture and Life Sciences at Texas A&M University invites applications for a full-time, 9-month, tenure-track Assistant Professor position in Artificial Intelligence (AI) for Horticultural Crop Systems. This position is part of a four-position cluster hire in AI in Agriculture in the College of Agriculture and Life Sciences aimed at building new research capacity and supporting the development of an undergraduate minor in AI-Enabled Agricultural Systems to prepare students for a rapidly expanding ag-tech workforce.
Within this cluster, the Horticultural Sciences position focuses on applying artificial intelligence to address core biological and production challenges in horticultural crops, including but not limited to variable environments, crop load balance, water use, and disease pressure. The position is grounded in plant biology, with an emphasis on understanding and modeling plant growth, yield, quality, and stress responses across a wide range of horticultural productions systems ranging from annual crops to long-lived perennials and tree crops, and integrating plant, environmental, and management processes.
This position focuses on the development of models that connect horticultural crop processes with production outcomes and support both discovery and application. These models will improve understanding of plant performance across environments while informing key management decisions such as irrigation scheduling, harvest timing, crop load management, and responses to biotic and abiotic stress.
Model development will be supported through the integration of diverse data sources, including but not limited to environmental sensing, canopy imaging, biosensors, genomic data, and image-based phenotyping, combined with machine learning methods that leverage large-scale datasets. These efforts will lead to the development of decision-support systems for horticultural crop production that improve management efficiency, enhance resilience for existing producers, and lower barriers for new entrants to adopt horticultural systems.
We are seeking candidates with a strong background in horticulture, plant sciences, or crop systems who also have expertise in artificial intelligence, machine learning (ML), or data analysis. Candidates should be interested in applying AI across scales, from field and greenhouse systems to plant and molecular levels, and in linking data with biological understanding to address both practical production questions and fundamental aspects of plant performance. The successful candidate will establish a nationally and internationally recognized research and teaching program that integrates artificial intelligence with horticultural science to address challenges facing producers, including weather variability, water scarcity, labor constraints, pest and disease pressure, and market uncertainty.
Research areas may include, but are not limited to:
• Application of AI to address key biological and production challenges in horticultural systems, with a focus on improving decision-making related to crop growth, yield, quality, and resource use to enhance economic returns
• Development of models that capture biological and structural variability across crops, from annuals to long-lived perennials and tree crops
• Integration of data from environmental sensing, imaging, phenotyping, and genomic sources to understand and predict plant performance
• Design of decision-support tools that translate model outputs into actionable strategies for irrigation, crop load management, and stress response
The faculty member will collaborate across Texas A&M AgriLife Research, Texas A&M AgriLife Extension, the College of Agriculture and Life Sciences, and industry partners. Opportunities exist to engage with major Texas horticultural industries, including viticulture and enology, citrus, pecans, vegetables, controlled environment horticulture, urban horticulture, and ornamental and nursery production, as well as applications in landscape and commercial systems. The successful candidate will be committed to advancing innovation and delivering solutions that support the land-grant mission of Texas A&M University.
Major Duties and Responsibilities
The successful candidate will develop an innovative, externally funded research program that solves key biological questions in horticultural science by application of artificial intelligence approaches. This includes conducting original research that results in high-impact, peer-reviewed publications and advances sustainable, profitable horticultural systems. The candidate will focus on biological questions of economic importance in horticultural crops and integrate artificial intelligence with data science, sensing technologies, forecasting, and decision frameworks to increase profitability and reduce risks by enhancing water efficiency and sustainable production, disease protection, precision nutrition, and food quality in high-value horticultural crops. The candidate is expected to lead innovations that advance sustainable horticultural production systems that strengthen Texas's economy and enhance nutrition and food quality, thereby promoting healthy living.
The candidate will develop and teach new courses, including a three-credit course in Decision-Centric AI for Horticultural Crop Production, which will be part of an 18-credit minor in AI-Enabled Agricultural Systems, emphasizing 'literacy in AI'. As learning outcomes, the students should be able to apply AI and machine learning to address natural resource problems, with attention to uncertainty and responsible use; build and evaluate models using agricultural data streams (field sensors, imagery, genomics/phenomics and economic data); translate model outputs into actionable decisions to improve profitability, sustainability, and resilience; communicate results to technical and non-technical stakeholders and evaluate adoption, risks, and policy considerations. An AI in Agriculture Studio/Practicum (industry/AgriLife project-based capstone) will also be part of the AI minor. Other courses may be assigned as needed by the department. The candidate will mentor graduate students, undergraduate researchers, and postdoctoral scholars, while inspiring the next generation of horticultural scientists to serve Texas and beyond.
Service expectations include making contributions to Department, College, and University, as well as actively participating in professional societies. The individual will also be expected to engage with growers, commodity groups, and technology industries across Texas, supporting Texas A&M's land-grant mission to serve the state through teaching, research, and outreach that address real-world challenges.
Effort Distribution: 60% research, 30% teaching, and 10% service.
The anticipated start date for the position is January 4, 2027.
Qualifications
Required Qualifications
• A Ph.D. primarily in horticultural sciences, plant sciences, agronomy, biology, or a related field, with additional training in Artificial Intelligence and a strong emphasis on horticultural crops; or a Ph.D. in AI/ML or data sciences must be accompanied with a strong background in plant systems.
• Demonstrated ability or potential to secure extramural funding and develop a productive research program.
• Evidence of effective teaching and mentoring.
• Excellent scientific communication skills
Preferred Qualifications
• Experience in studying plant biological questions and applying artificial intelligence technologies in horticultural crops.
• Robust statistical skills and experience in analyzing large datasets and data fusion.
• Engagement in sensor systems, computer vision, robotics, and remote sensing.
• Integration of crop modeling, phenomics and plant physiology.
• Computational skills, including programming languages, coding, software development, and artificial intelligence.
• A proven track record of publications in high-impact, peer-reviewed horticultural research journals.
• Record of interdisciplinary collaborations and/or stakeholder engagement.
• Familiarity with challenges and opportunities relevant to Texas horticulture.
Application Instructions
Applicants must submit:

• A cover letter (2-page limit)
• Curriculum Vitae
• Personal statement to include philosophy and plans for research, teaching & service (single document; 3-page limit)
• Contact information for three references.

Applications will only be accepted online at apply.interfolio.com/187771.
Applications will be reviewed beginning August 10, 2026, and will continue until the position is filled. The anticipated start date for the position is January 4, 2027.
Direct inquiries to:
Dr. Isabel Vales, Search Committee Chair
Department of Horticulture Sciences
Email: isabel.vales@agnet.tamu.edu