Postdoctoral Research Associate

About the role

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 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, delivering practical soil and agronomic information for decision‑making at the sub‑field, farm, and regional levels.

Responsibilities

• 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.
• Integrate multi‑source datasets and analyze yield stability over time.
• Build and validate machine‑learning/AI‑based prediction models.
• Create field zones tied to management actions supported by farm economics.
• Develop scaling‑up solutions for different management scenarios.
• Develop profit–risk–environment trade‑off products.
• Build reusable R/Python workflows for automated reproducible analysis.
• Publish and present results in collaboration with USDA‑ARS and university partners across Texas and the U.S.
• Lead and co‑author peer‑reviewed scientific publications.
• Actively contribute to proposal development.
• Perform 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 impacts of management practices on environmental outcomes such as soil health diagnostics, water quality, carbon/nitrogen cycling, and profit–risk–environment trade‑off 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.

Benefits

• 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.

Pay

Compensation for this position is commensurate based on the selected candidate’s qualifications.