Description
The School of Agricultural and Natural Sciences (SANS) at the University of Maryland Eastern Shore (UMES) invites applications for a full-time, tenure-track faculty position in Artificial Intelligence for Agriculture. We seek a creative and motivated individual working at the interface of AI, data science, computing, and agricultural or environmental systems, who will bring demonstrated experience applying AI tools to agriculture. The successful candidate will have strong domain expertise and a clear aptitude and motivation to develop AI and data science capabilities in this rapidly advancing field.
This strategic hire aims to strengthen UMES’s capacity in applied research, innovation, teaching, and Extension programming in support of its 1890 land-grant mission. Candidates who already lead work in this space and those who show strong potential to grow into an impactful, collaborative program are encouraged to apply.
This is a 9-month, tenure-track assistant professor position with an anticipated appointment distribution of 45% research, 45% Extension, and 10% Teaching. The successful candidate is expected to develop a nationally recognized, externally funded program in artificial intelligence with relevance to agriculture.
About UMES: The University of Maryland Eastern Shore (UMES) is an 1890 Land-Grant University located on Maryland’s Eastern Shore, with a mission to provide educational, research, and Extension leadership that advances agricultural innovation. The School of Agricultural and Natural Sciences (SANS) offers a collaborative environment where faculty work across disciplines (from biotechnology, animal sciences, and soil health to engineering and data science) to address challenges in food, energy, and environmental systems. UMES is on the Delmarva Peninsula between the Atlantic Ocean and Chesapeake Bay, with the major metropolitan areas of Washington, D.C., Baltimore, MD, and Philadelphia, PA, within easy travel distance.
Salary: $80,000-$95,000
Benefits: The University of Maryland Eastern Shore, as a University System of Maryland institution and a Maryland State agency, provides a comprehensive benefits package to all regular faculty and
staff. The Office of Employee Benefits provides consultative services and assistance with benefits planning, enrollment, and changes. Eligible employees may participate in a variety of benefit plans including:
Health insurance, including multiple medical plan options for employees
and dependents offered
through the State of Maryland Employee Benefits Division.
Prescription drug, dental, and flexible spending accounts, and vision
coverage.
Retirement plans: mandatory enrollment in a state pension system or an
Optional Retirement Plan with Fidelity or TIAA, Supplemental Retirement
Accounts (TIAA, Fidelity, or MSRP-Nationwide) with $600 annual state
match, Life Insurance (state sponsored MetLife, USM
sponsored MetLife Plan, life insurance and long-term disability insurance).
Tuition remission benefits for eligible employees and, subject to USM
policies, spouses and dependents at University System of Maryland
institutions.
Leave benefits include paid sick leave (15 days), collegial (3 days per year),
and paid holidays.
Employee wellness and support resources and access to the State of
Maryland wellness programs.
The University is committed to the success of incoming faculty. The successful candidate will be supported by capacity development funding, along with mentoring, collaborative grant development, and access to field and demonstration sites. Eligible employees may participate in the University System of Maryland benefits package.
The successful candidate will join a growing group of faculty working across agricultural and natural sciences, Extension, engineering, data science, and environmental systems, with opportunities to collaborate with UMES Extension professionals, the UMES Agricultural Experiment Station, University of Maryland Extension, USDA agencies, other 1890 and 1862 land-grant institutions, industry partners, and regional producers.
Additional Job Details
Required Application Materials:
Screening of applications will be September 15, 2026. Qualified applicants must submit the following materials:
A cover letter summarizing qualifications, describing interest in the position and alignment with the UMES land-grant mission
Curriculum vitae
Statement of research interests and future research plans (maximum 2 pages)
Statement of teaching philosophy (1 page)
Statement of Extension philosophy (1 page)
Unofficial graduate transcripts
Contact information for three professional references, current or past supervisor (references will not be contacted without prior consent).
All applicants must apply using the new online application system. Please visit https://umd.wd1.myworkdayjobs.com/UMES to apply. The successful candidate must be able to show acceptable documentation establishing the right to accept employment in the United States of America without employer sponsorship.
Questions regarding the position responsibilities should be directed to Dr. Purushothaman Natarajan, Department of Agriculture, by email: [email protected]
Best Consideration Date: September 15, 2026
Posting Close Date: N/A
Open Until Filled: Yes
Requirements
Responsibilities:
Conduct applied and translational research leading to improved
productivity, resource efficiency,
and environmental stewardship in agricultural systems
Collaborate with UMES Extension professionals to translate research into
practical tools, demonstrations, and stakeholder training
Develop or contribute to competitive grant proposals and collaborative
projects with UMES faculty, other institutions, and industry partners
Engage in interdisciplinary teams across SANS and beyond to integrate AI
and data-driven approaches into agricultural innovation
Required Qualifications:
Ph.D. (completed or near completion) in Agricultural Engineering, Computer
Science, Plant or Animal Science, Data Science, Statistics, Environmental
Science, or a related discipline
Demonstrated experience with (or strong demonstrated potential and
motivation to develop) data analytics, modeling, or AI applications in
agriculture, natural resources, or allied fields.
Evidence of research productivity and strong potential for program
development
Effective communication, collaboration, and mentoring skills
Qualifications: (Preferred)
Experience working with AI/ML tools and field-deployed technologies (e.g.,
sensors, drones, or robotics)
Experience working with Extension, farmers, or industry stakeholders
Demonstrated success or strong potential in grant writing and collaborative
research
Physical Demands:
May require extended periods of standing, bending, stooping, sitting at
desk.
May require lifting.
Requires communication with a variety of constituents externally and
internally.
Requires operation of a variety of office equipment.
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