**38667BR** **Extended Job Title:** TTU Post Doc Remote Sensing & AI for Ag Water Sustainability **Position Description:** Performs specialized Post Doctoral work in the planning, conducting and/or supervision of original research. Responsible for participating in a research project associated with PhD studies and the interpretation of the results of publication. Work is performed under supervision of graduate faculty members with evaluation based on accomplishment of assigned objectives and overall effectiveness of project. May supervise research and student assistants. **Requisition ID:** 38667BR **Travel Required:** Up to 25% **Major/Essential Functions:** • Develop new indicators and tools to enhance water conservation and sustainability across producer fields based on data from soil sensors, satellite imagery-based machine learning and AI tools. • Evaluate different soil moisture sensors and satellite data-based approaches for improving crop water productivity and water management in West Texas and Southern High Plains. • Application of high-resolution satellite data (SMAP, Sentinels, Landsats etc.) and drone images using Machine learning and AI techniques for mapping soil moisture dynamics, irrigation water requirements, crop type mapping, extracting phenology and monitoring agricultural droughts. • Create irrigation scheduling approaches and check crop water status through moisture mapping based on SMAP products. • Access crop water productivity at different spatial temporal scales and under different climate change scenarios. • Utilize satellite images to develop tools to predict biomass (forages) and crop yield including greenhouse gas emissions under different cropping patterns in Southern High plains • Collect field based data as needed for ground truthing model outputs and draft high impact peer review publications **Grant Funded?:** Yes **Pay Basis:** Monthly **Work Location:** Lubbock **Preferred Qualifications:** Ph.D. in remote sensing, geography, computer science, irrigation management, soil and water engineering, agronomy, or crop science. Demonstrable experience working with remote sensing data, machine learning and AI techniques, image analysis, handling future climate data and programming in Python/R. The candidate should have the ability to handle large datasets, excellent analytical skills and drafting peer-reviewed publications. . Previous research experience in satellite remote sensing, machine learning and AI applications in agriculture and irrigation water management with good knowledge of programming languages R/Python would be preferred. **Department:** Plant and Soil Science **Required Attachments:** Cover Letter, Professional/Personal References, Research Statement, Resume / CV **Job Type:** Full Time **Job Group:** Research Staff **Shift:** Day **Required Qualifications:** PhD in area of project specialization. Knowledge of modern research practices, the methods, resources, and standards thereof. Ability to organize work effectively, conceptualize and prioritize objectives and exercise independent judgment based on an understanding of organizational policies and activities. Ability to integrate resources, policies, and information for the determination of procedures, solutions and other outcomes. Ability to establish and maintain effective work relationships with other employees and the public. Ability to plan and allocate the workload of employees, providing direct training and supervision as needed. **Does this position work in a research laboratory?:** Yes **About the Department and/or College:** The Davis College Water Center at Texas Tech University (Lubbock, TX) invites applications for a Post Doc position focusing on cutting-edge research in use of satellite based remote sensing in tandem with ground-based sensor and machine learning/AI tools using satellite imagery for agricultural water management. The position requires a wide range of knowledge and skills that cover aspects related to working with remotely sensed data in terms of satellite images, AI and ML for image analysis, sensors for irrigation water management and resource conservation. This position offers an exciting opportunity for researchers with expertise in remote sensing, machine learning and big data analytics to contribute to innovative projects addressing critical challenges in Ag water sustainability. As a Post-Doc, the successful candidate will be engaged in various aspects of research, from field scale experiments to the development and implementation of state-of-the-art tools and approaches for water conservation, using ground sensors, aerial imaging, and remote sensing to enhance Ag water productivity. This is a three-year position with an available start date of October 15, 2024; however, the start date can be flexible. Applicants must utilize the Texas Tech University job portal to apply. Inquiries can be sent to Dr. Krishna Jagadish (kjagadish.sv@ttu.edu). Please use “Post doc – Remote Sensing and AI for Ag Water Sustainability” in the subject line. **Special Instructions to Applicants:** This is a three-year position with an available start date of October 15, 2024; however, the start date can be flexible. Applicants must utilize the Texas Tech University job portal to apply. Inquiries can be sent to Dr. Krishna Jagadish (kjagadish.sv@ttu.edu). Please use “Post doc – Remote Sensing and AI for Ag Water Sustainability” in the subject line. **Safety Information:** Adherence to robust safety practices and compliance with all applicable health and safety regulations are responsibilities of all TTU employees. **Pay Statement:** Compensation is commensurate upon the qualifications of the individual selected and budgetary guidelines of the hiring department, as well as the institutional pay plan. For additional information, please reference the institutional pay plan by visiting www.depts.ttu.edu/hr/payplan. **EEO Statement:** All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, disability, genetic information or status as a protected veteran. **About the University:** Established in 1923, Texas Tech University is a Carnegie R1 (very high research activity) Doctoral/Research-Extensive, Hispanic Serving, and state-assisted institution. Located on a beautiful 1,850-acre campus in Lubbock, a city in West Texas with a growing metropolitan-area population of over 300,000, the university enrolls over 40,000 students with 33,000 undergraduate and 7,000 graduate students. As the primary research institution in the western two-thirds of the state, Texas Tech University is home to 10 colleges, the Schools of Law and Veterinary Medicine, and the Graduate School. The flagship of the Texas Tech University System, Texas Tech is dedicated to student success by preparing learners to be ethical leaders for a diverse and globally competitive workforce. It is committed to enhancing the cultural and economic development of the state, nation, and world. About Lubbock:Referred to as the “Hub City” because it serves as the educational, cultural, economic, and health care hub of the South Plains region, Lubbock boasts a diverse population and a strong connection to community, history, and land. With a mild climate, highly rated public schools, and a low cost of living, Lubbock is a family-friendly community that is ranked as one of the best places to live in Texas. Lubbock is home to a celebrated and ever-evolving music scene, a vibrant arts community, and is within driving distance of Dallas, Austin, Santa Fe, and other major metropolitan cities. Lubbock’s Convention & Visitors Bureau provides a comprehensive overview of the Lubbock community and its resources, programs, events, and histories.