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.