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Closing Date:
Type of Position:
Faculty - Tenure/Tenure Track
Workstudy Position:
No
Job Type:
Regular
Work Shift:
Sponsorship Available:
No
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:
AES | HORT | Horticulture
Department's Website:
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: The successful candidate will be responsible for the following:
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,…