Job Title

Assistant Research Scientist

Agency

Texas A&M Agrilife Research

Department

Temple

Proposed Minimum Salary

Commensurate

Job Location

Temple, Texas

Job Type

Staff

Job Description

The selected candidate would assist a team of ecosystem modeling scientists to perform process-based ecosystem models based research and develop decision support systems. The candidate would also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more efficient and reliable.

Responsibilities:

• Aids in the development and application of national scale modeling frameworks for water and crop management. Prepare and process large datasets for use in national model assessments conducted with SWAT/SWAT+.

• Aids in the development of software and tools to support large- and small-scale modeling efforts.

• Integrates ML/AI with Process-based modeling to develop/optimize decision support systems

• Works effectively within a modeling group comprised of ARS, AgriLife, and other personnel. Actively participates in joint research activities. Effectively manages and completes assigned tasks.

• Other job-related duties as required.

Required Education and Experience:

• Ph.D. in Ecology, Hydrology, Geology, Environmental Science/Engineering, Civil Engineering, or related disciplines with emphasis on surface hydrology or watershed assessment.

• Relevant professional experience.

Required Knowledge, Skills, and Abilities:

• Demonstrated publication record in hydrological or water quality modeling and analysis.

• Interdisciplinary teamwork skills with researchers across different disciplines.

• Flexibility to perform work in a team or individually with supervision.

• Good communication, interpersonal skills, professionalism, and competency.

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

Preferred Knowledge, Skills, and Abilities:

• Knowledge of computer models on watershed assessment.

• Knowledge of programming or scripting languages such as Python, Fortran, R, or others.

• Experience in remote sensing data analysis and geographic information systems.

• Experience in machine learning-motivated algorithms and quantitative data analysis.

• Strong writing and communication skills.

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/Affirmative Action/Veterans/Disability Employer.