Description

Precision tools powered by artificial intelligence (AI) are essential for adapting the tree fruit industry to a rapidly changing climate because they enable growers to monitor and manage environmental variables with high accuracy. Graduate student fellowships are currently available at Penn State University for doctoral work on the AI enhanced fruit production systems. Some examples of research topics include AI-based precision ag tools development, precision crop load management, and precision weed management. In a long term, this program will enhance the resilience of tree fruit production systems under climate stressors like extreme temperatures, irregular rainfall, and accompanying biotic (pests, diseases, and weeds) pressures. 

The successful candidates will enter in Fall 2026 or Spring 2027 as a cohort (an interdisciplinary group) under a USDA-funded project. The accepted students will receive transdisciplinary training and cross-departmental mentorship to advance research and enhance impact. Cohort students will receive and help shape cohort building activities including training in precision agricultural technologies related tools and analysis, a unique transdisciplinary tree fruit seminar series, mentoring of undergraduate students, grantsmanship and science communication, and various opportunities on professional development. 

Candidates must apply and be admitted to one of the graduate programs below. To be considered for an AI for Tree Fruit Production cohort fellowship, candidates are strongly encouraged to apply before June 30, 2026. Candidates must be citizens or nationals of the USA, per program requirements. Contact the faculty member listed below in your discipline of interest with CV. The subject of the email should be ‘USDA AI Tree Fruit PhD Application’. Do not add any other information on the subject line.

      Agricultural and Biological Engineering

                https://abe.psu.edu/graduate/admissions 

                Long He, Associate Professor, luh378@psu.edu 

      Agricultural and Environmental Plant Science

                 https://plantscience.psu.edu/graduate/admissions/aeps 

                Shanthanu Krishna Kumar, Assistant Professor,shan.kumar@psu.edu – Tree Fruit Production

                Caio Brunharo, Assistant Professor,brunharo@psu.edu –Weed Management 

Commitment and demonstrated ability to work both independently and as part of a team are required. All the students will be funded by a USDA NIFA funded project and research and extension assistantships for four years. Each position includes a competitive stipend, summer support, tuition waiver, and health insurance. Cohort students will have the opportunity to work with ongoing Penn State AI and Precision Ag related initiatives such as:

      Technologies for Agriculture and Living Systems (TALIS)

      Center for Artificial Intelligence Foundations and Engineered Systems (CAFE)

      Other collaborative research projects among the team members

Requirements

Educational and Citizenship Requirements

Bachelor's degree or equivalent in agriculture, engineering, plant science, computer science, or related field (masters degree preferred)                                            U.S. citizen or national status (required per program guidelines)
Eligibility for admission to one of the participating Penn State graduate programs (Agricultural and Biological Engineering, or Agricultural and Environmental Plant Science)

Technical and Research Skills

Demonstrated experience or strong aptitude in precision agriculture, agricultural technology, or crop production systems
Proficiency in data analysis, programming, or software development (preferred)
Familiarity with AI/machine learning concepts or willingness to develop expertise in this area
Experience with field research, experimental design, or agricultural systems management (preferred)

Professional Competencies

Strong written and verbal communication skills for scientific and professional audiences
Ability to work independently on research objectives while contributing effectively to team-based projects
Commitment to interdisciplinary collaboration and cross-departmental mentorship
Initiative in professional development, including grant writing, science communication, and publication

Program Commitment

Willingness to engage in cohort-building activities and transdisciplinary training
Availability to mentor undergraduate students and participate in extension/outreach activities
Flexibility to begin doctoral studies in Fall 2026 or Spring 2027