Postdoctoral Research Associate

About the role

Texas A&M AgriLife Research seeks a Postdoctoral Research Associate to support a USDA-funded project evaluating concentrated animal feeding operations (CAFOs) and manure management systems using the APEX agroecosystem model.

Responsibilities

• Conduct comprehensive literature reviews and gap analyses on regenerative animal production systems, manure management in CAFOs, and C–N cycling in soils, vegetation, manure, and livestock.
• Acquire, curate, and analyze field measurement datasets and associated environmental and economic information for model parameterization and validation.
• Develop or enhance model algorithms simulating carbon and nutrient budgets under varying manure housing and management practices using scientific programming languages.
• Implement newly developed modules and improvements into the APEX ecosystem simulation model.
• Assess agroecosystem C–N cycling dynamics influenced by concentrated ruminant-livestock operations and changing environmental conditions.
• Evaluate and refine the performance of the enhanced model across various dairy systems and livestock/grazing management scenarios.
• Document model development processes and disseminate research findings through peer-reviewed publications and technical reports.
• Perform other duties as assigned.

Requirements

• Ph.D. in Agricultural Sciences, Animal Science, Rangeland Management, Environmental Sciences, or a closely related discipline.
• Demonstrated record of peer-reviewed publications.
• Experience in designing, analyzing, and interpreting data from field studies.
• Strong project management and technical writing capabilities.
• Ability to work both independently and collaboratively.
• Strong organizational skills and ability to manage multiple tasks simultaneously.
• Ability to multi-task and work cooperatively with others.

Preferred Qualifications

• Proficient understanding of factors governing carbon and nitrogen cycling in farm-scale CAFO operations.
• Prior experience with process-based models such as EPIC, APEX, RUFAS, BCSM, GLEAM, or similar simulation frameworks.
• Proficiency in scientific programming (e.g., Python, Fortran) for data processing, model development, and computational analysis.