Assistant Professor - Integration of Omics in Plant Breeding

About the role

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Closing Date

• Type of Position: Faculty - Tenure/Tenure Track
• 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.

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Department: AES | HORT | Horticulture

Summary of Job Duties

This position is ideal for a visionary, builder-type scientist with the ambition to establish a nationally recognized program in molecular plant breeding, agricultural data analytics, and applied computational breeding. The successful candidate will integrate multi-omics data, statistical genetics, and modern computing approaches to deliver actionable tools for breeders. We seek a thought leader who can pair deep technical expertise with the ability to create practical, breeder-friendly solutions and foster collaborations across crops and disciplines.

Responsibilities

Research (80%)

• Develop and implement a cutting-edge, extramurally funded research program focused on computational breeding, multi-omics integration, AI-assisted decision support, and applied genomics for plant improvement.
• Collaborate with UADA plant breeders to modernize selection pipelines, such as through the use of genomic prediction, GWAS, QTL mapping, metabolomics, and/or high-throughput phenotyping.
• Translate quantitative genetic and statistical approaches into breeder-friendly platforms, apps, dashboards, and analytical workflows that facilitate data-driven decision-making.
• 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.
• Leverage existing computing infrastructure, including the Arkansas High Performance Computing Center (AHPCC,) to manage large, complex datasets and implement advanced analytic pipelines.
• Collaborate with faculty across departments, contributing to interdisciplinary initiatives that accelerate crop improvement and the adoption of modern breeding strategies.

Teaching (20%)

• Support and mentor graduate students in applied computational and genomic projects, providing hands-on training in data analysis, workflow optimization, and experimental design.
• Teach annually one undergraduate course in plant genetic resources/crop evolution or a related area aligned with plant breeding applications and one graduate course in quantitative genetics.
• Contribute to curriculum innovation aligned with emerging molecular plant breeding tools, 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.
• Access to the Arkansas High-Performance Computing Cluster (AHPCC).
• Synergies with cluster hires in Phenomics Applied to Plant Breeding and Rice Genomics and Breeding Systems, and a supportive multi-crop breeding ecosystem, including established programs in fruits, vegetables, soybean, and rice.
• Opportunities for cross-department collaboration with researchers in agricultural engineering, agronomy, entomology, food science plant pathology, soil science, and weed science.

Minimum Qualifications

• Ph.D. in Plant Science, Plant Molecular Biology, Plant Breeding, Genetics, Genomics, Data Science, AI/ML, or a closely related discipline or highly related field. Ph.D. must be conferred by the date of hire.
• Evidence of scholarly productivity in plant breeding and quantitative trait analysis, genomic breeding tools, statistical genetics, or data analytics
• Excellent demonstrated verbal and written communication skills
• Demonstrated interpersonal skills and ability to collaborate with multidisciplinary teams and applied breeding programs

Preferred Qualifications

• Experience applying and translating plant production and plant breeding programs and information to support decision-making and adoption of modern breeding strategies
• Experience in team collaboration and leadership
• Demonstrated effective grantsmanship and ability to secure competitive funding
• Experience with diverse audiences and stakeholders
• Demonstrated commitment to student training and development and teaching skills to facilitate learning in undergraduate and graduate students

Salary Information

Commensurate with education and experience.

Required Documents to Apply

Cover Letter/Letter of Application, Curriculum Vitae, List of three Professional References (name, email, business title), Statement of Research Philosophy, Statement of Teaching Philosophy, Unofficial/Official Transcript(s)

Special Instructions to Applicants

Recruitment Contact Information: Dr. Margaret Worthington

Associate Professor

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

Criminal Background Check, 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
• Frequent Physical Activity: Driving, Feeling, Hearing, Repetitive Motion, Talking, Walking
• Occasional Physical Activity: N/A

Benefits Eligible

Yes