Postdoctoral Researcher in Agricultural & Environmental Modeling

tamus; Temple (TX); On-site; USD 70,000 - 100,000; Full time

Job summary

Texas A&M AgriLife Research in Temple, Texas, invites applications for a Postdoctoral Research Associate position in Agricultural, Animal, Rangeland, or Environmental Sciences. The role focuses on enhancing the APEX model to simulate environmental and economic impacts of CAFO operations, with work spanning data curation, model development, and field validation.

The successful candidate will contribute to research on carbon and nitrogen cycling, work with diverse datasets, and collaborate across

Qualifications

• 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.

Responsibilities

• Conduct literature reviews and gap analyses on regenerative animal production systems and manure management in CAFOs.
• Acquire, curate, and analyze field data for model parameterization and validation.
• Develop or enhance model algorithms for carbon and nutrient budgets under varying manure practices.
• Implement modules and improvements into the APEX ecosystem simulation model.
• Document development processes and disseminate findings via publications and reports.

Skills

Project management

Technical writing

Independent work

Team collaboration

Data analysis

Education

Ph.D. in Agricultural Sciences or related field

Tools

Python

Fortran

Job description

Texas A&M AgriLife Research in Temple, Texas, invites applications for a Postdoctoral Research Associate position in Agricultural, Animal, Rangeland, or Environmental Sciences. The role focuses on enhancing the APEX model to simulate environmental and economic impacts of CAFO operations, with work spanning data curation, model development, and field validation.

The successful candidate will contribute to research on carbon and nitrogen cycling, work with diverse datasets, and collaborate across