Assistant Professor

About the role

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Closing Date

• Type of Position: Research
• Workstudy Position: No
• Job Type: Regular

Sponsorship Available: Yes

Institution Name: Division of Agriculture of the University of Arkansas

The University of Arkansas System Division of Agriculture is a state wide campus, with faculty based on University campuses, at Research and Extension Centers and in every Arkansas county. It consists of the Arkansas Agricultural Experiment Station (AES) and the Arkansas Cooperative Extension Service (CES), and is home to more than 1400 employees.

The Division was established in 1959 and is headed by the Vice-President for Agriculture. The Division headquarters is located in Little Rock with the rest of the University of Arkansas System Administration. As an employer, the University of Arkansas System Division of Agriculture offers a vibrant work environment and a workplace culture that promotes a healthy work-life balance.

Below you will find the details for the position including any supplementary documentation and questions you should review before applying for the opening. To apply for the position, please click the Apply link/button.

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Department: CSES | Crop, Soil and Environmental Sciences

Summary of Job Duties

As part of a cluster hire in multi-omics integration and data analytics applied to plant breeding, the University of Arkansas Division of Agriculture invites applications for a 12-month, tenure-track Assistant Professor position (80% research, 20% teaching) in Phenomics Applied to Plant Breeding.

This is a unique opportunity to join a coordinated cohort of established and new faculty working to modernize and transform public breeding programs across Arkansas.

The successful candidate will develop a comprehensive research program focused on high-throughput phenotyping, AI and machine learning-based trait extraction, and data-driven selection strategies that accelerate genetic gain and strengthen applied breeding pipelines across multiple crops.

Responsibilities

Research (80%)

The successful candidate will be expected to

• Develop a cutting-edge research program focused on high-throughput phenotyping, image-based trait extraction, sensor integration, and advanced data analytics applied to plant breeding.
• Utilize and innovate in sensing platforms including UAVs, robotics, ground-based systems, multispectral and hyperspectral imaging, LiDAR, satellite systems, automated greenhouse phenotyping, and related technologies.
• Apply AI, machine learning, statistical modeling, and computer vision to quantify complex traits, improve prediction accuracy, and enable earlier and more precise selection decisions.
• Collaborate directly with breeders in soybean, rice, fruits, vegetables, and wheat to integrate phenomics outputs into active selection pipelines.
• Establish interdisciplinary partnerships with weed scientists, soil scientists, agronomists, plant pathologists, and agricultural engineers to expand phenotyping applications.
• Secure extramural funding from federal agencies (USDA-NIFA, NSF, DOE, NASA, etc.), commodity boards, interdisciplinary initiatives, and industry partnerships.
• Publish research findings in peer-reviewed journals, present at scientific conferences, and communicate results to stakeholders and breeding teams.

Teaching (20%)

The successful candidate will be expected to

• Teach one undergraduate and one graduate course annually in remote sensing, phenomics, data analytics, machine learning, or a related area aligned with plant breeding applications.
• Mentor M.S. and Ph.D. graduate students and engage undergraduate students.
• Contribute to curriculum innovation aligned with emerging sensing, computational, and data science technologies in agriculture.

Program Resources and Collaborative Advantages

The successful candidate will benefit from

• Access to AAES's statewide network of research and extension stations, including five Research & Extension Centers and several Research Stations located across Arkansas. These sites provide diverse soil, climate, and production environments to support diverse environments for phenotyping deployment and validation.
• Access to the Arkansas High-Performance Computing Cluster (AHPCC).
• Synergies with cluster hires in omics integration, AI/data analytics, and genomics, and a supportive multi-crop breeding ecosystem, including established programs in soybean, rice, fruits, and vegetables.
• Opportunities for cross-department collaboration with researchers in weed science, soil science, agronomy, plant pathology, agricultural engineering, and food science.

Location

This position is based at the University of Arkansas campus located in Fayetteville, AR, a welcoming community ranked as one of the best places to live in the U.S. The growing region surrounding Fayetteville is home to numerous Fortune 500 companies and one of the nation's strongest economies. Northwest Arkansas is quickly gaining a national reputation for its focus on the arts and overall quality of life.

Department

The Department of Crop, Soil, and Environmental Sciences is one of eight academic departments in Dale Bumpers College of Agricultural, Food and Life Sciences and the University of Arkansas Division of Agriculture, along with the School of Human Environmental Sciences. Resident instruction is provided by 16 faculty members at the Fayetteville campus with approximately 140 undergraduate majors and 60 graduate students.

An additional 12 Research and Extension faculty serve clientele at various Research and Extension Centers strategically located around the state. The Department offers Bachelor's degrees in Crop Science and Environmental, Soil, and Water Sciences, along with Master's and Doctoral degrees.

The department is in the process of hiring several new faculty members and the incumbent will join an energetic and collaborative cohort of assistant professors. More information regarding the Department of Crop, Soil, and Environmental Sciences, and the University of Arkansas can be obtained by visiting the website:

Application

To be considered, applicants must submit the following materials: 1) Letter of application including a summary of relevant experiences and accomplishments; 2) A vision statement regarding your goals in research for this position; 3) A detailed vitae including a list of publications, funding, and a summary of research and mentoring or teaching activities; 4) Official academic transcripts; and 5) List of three references with mailing and e-mail addresses and phone numbers.

Deadline

Screening of applicants will begin Dec 4, 2026, and will continue until a qualified candidate is identified.

Qualifications

Required

• Ph.D. in Plant Science, Agricultural Engineering, Remote Sensing, Data Science, AI/ML, Plant Breeding, or a closely related discipline. Degree must be conferred prior to the hire date.
• Evidence of scholarly productivity in phenomics, sensing systems, machine learning, computer vision, quantitative trait analysis, or related fields.
• Strong communication skills and ability to collaborate with multidisciplinary teams.

Preferred

• Experience applying phenomics tools in plant breeding.
• Experience with UAV operations, sensor integration, robotics, computer vision pipelines, or geospatial analytics.
• Demonstrated ability to secure competitive funding.
• Demonstrated commitment to student training and development.

Commensurate with education and experience

Required Documents to Apply

Cover Letter/Letter of Application, Curriculum Vitae, Listing of Publications, List of three Professional References (name, email, business title), Other (see special instructions for details), Statement of Research Philosophy, Unofficial/Official Transcript(s)

Special Instructions to Applicants

Applicants should submit the following: 1) Letter of application including a summary of relevant experiences and accomplishments; 2) A vision statement regarding your goals in research for this position; 3) A detailed vitae including a list of publications, funding, and a summary of research and mentoring or teaching activities; 4) Official academic transcripts; and 5) List of three references with mailing and e-mail addresses and phone numbers.

Recruitment Contact Information

• All application materials must be uploaded to the University of Arkansas System Career Site
• Please do not send to listed recruitment contact.

Pre-employment Screening Requirements

Motor Vehicle Reports Check

The University of Arkansas System Division of Agriculture may conduct pre-employment background checks on certain positions for applicants being considered for employment. The background checks may include a criminal background check and a sex offender registry check. Required checks are identified in the position listing.

A criminal background check or arrest pending adjudication information alone shall not disqualify an applicant in the absences of a relationship to the requirements of the position. Background check information will be used in a consistent, non-discriminatory manner consistent with the state and federal law.

• Persons must have proof of legal authority to work in the United States on the first day of employment.
• All application information is subject to public disclosure under the Arkansas Freedom of Information Act.

Constant Physical Activity

Manipulate items with fingers, including keyboarding, Repetitive Motion, Sitting, Standing, Talking

Frequent Physical Activity: Grasping, Hearing, Kneeling, Lifting

Occasional Physical Activity: Balancing, Driving, Walking

Benefits Eligible

Yes