Postdoctoral Research Associate

Postdoctoral Research Associate

Texas A&M AgriLife Research at Temple is seeking a highly motivated Postdoctoral Research Associate with expertise in precision agriculture technologies, digital soil mapping/pedometrics, proximal/remote sensing, and geospatial modeling. The ideal candidate will work and collaborate closely within a research team at Texas A&M AgriLife and USDA-ARS laboratories to advance precision conservation in cropping systems with diverse management, delivering practical soil and agronomic information for decision-making at the subfield, farm, and regional levels.

Responsibilities:

The selected candidate will combine field observations with proximal sensing, UAV and satellite imagery, yield monitor data, and soil, environmental, and weather datasets to create soil and agronomic intelligence products that guide precision management at the sub-field level and inform conservation decisions. The role includes integrating multi-source datasets, analyzing yield stability over time, building and validating ML/AI-based prediction models, creating field zones tied to management actions supported by farm economics, and developing scaling-up solutions for different management scenarios. The researcher will develop profit–risk–environment tradeoff products, build reusable R/Python workflows, and publish and present results in collaboration with USDA-ARS and university partners across Texas and the U.S. In addition, leading and co-authoring peer-reviewed scientific publications, as well as actively contributing to proposal development, are key responsibilities. Performs other duties as assigned.

Required Qualifications:

• Ph.D. in Soil Science, Agronomy, Agricultural Engineering, Geosciences, Environmental Sciences, or a closely related discipline.

• Strong background in data-intensive soil and agronomic analytics and geospatial modeling.

• Proficiency in proximal sensing, GIS, and remote sensing.

• Ability to multi-task and work cooperatively with others.

Preferred Qualifications:

• Advanced ML/AI experience in digital soil mapping/pedometrics and soil landscape modeling, and in handling high-resolution geospatial and temporal datasets.

• Demonstrated experience with precision agriculture data/tools (yield monitor data, spatial variability, management zones, ECa/EMI, LiDAR, VisNIR, and UAV workflows).

• Proficiency in programming languages (R or Python) for automated reproducible workflows.

• Knowledge, experience, and interest in assessing the impacts of management practices on environmental outcomes, such as soil health diagnostics, water quality, carbon/nitrogen cycling, and profit–risk–environment tradeoff products.

• Excellent academic record, including authored/co-authored publications and contributions to significant scientific meetings, seminars, and conferences.

• Strong oral and written communication skills.

Other Requirements:

• This position is grant funded and availability is contingent on grant funding.

Salary: Compensation for this position is commensurate based on the selected candidate's qualifications.

Position Funding: This position is grant funded and availability is contingent on grant funding.

Why Work at Texas A&M AgriLife?

When you choose to work for Texas A&M AgriLife, you become part of an organization that is an established leader in agriculture and life sciences with a wide range of capabilities to meet the needs of our statewide, national, and international constituents.

In addition, Texas A&M AgriLife offers a comprehensive benefit package including the following:

• Health, dental, vision, life and long-term disability insurance with Texas A&M AgriLife contributing to employee health and basic life premiums
• 12-15 days of annual paid holidays
• Up to eight hours of paid sick leave and at least eight hours of paid vacation each month
• Automatic enrollment in the Teacher Retirement System of Texas
• Employee Wellness Initiative for Texas A&M AgriLife

Applicant Instructions:

Applications received by Texas A&M AgriLife must either have all job application data entered or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to prepopulate the online application.

Required Documents:

CV/ Resume

Cover letter

List of references

Copy of Degree/Transcript showing degree conferred

All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution's verification of credentials and/or other information required by the institution's procedures, including the completion of the criminal history check.

Equal Opportunity/Veterans/Disability Employer.