Job Details

Post Doctoral Research Associate - Agricultural Remote Sensing

Position Number: 9747720
Location: Lubbock, United States
Position Type: Agriculture - Other

Post Doctoral Research Associate - Agricultural Remote Sensing
Lubbock
45653BR
Plant and Soil Science

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.

About the University
Founded in 1923, Texas Tech University began with a mission to serve the needs of West Texas, but its impact has always reached far beyond. Today, Texas Tech, located in Lubbock (pop. 300,000+), is home to a vibrant community of more than 42,000 students.Texas Tech's 1,800-acre campus showcases Spanish Renaissance architecture and is home to one of the country's largest public art collections. Its 13 colleges include a prestigious School of Law and a distinguished School of Veterinary Medicine. These programs equip students with the skills and knowledge needed to excel in their respective fields. Built on the values of West Texas - hard work, grit and authenticity - the university graduates students who are deeply engaged in service to their communities and well-positioned to succeed in the world. Texas Tech is committed to achieving research and scholarly accomplishments that compare favorably to the member institutions of the Association of American Universities (AAU). For more than 100 years, Texas Tech has been a premier destination for those seeking a world-class education and a unique, personalized experience as a member of the Red Raider family.

About the Department and/or College
Davis College includes the departments of Agricultural and Applied Economics, Agricultural Education and Communications, Animal and Food Sciences, Landscape Architecture, Natural Resources Management, Plant and Soil Science, and Veterinary Sciences along with multiple research centers and institutes. The College has over 100 tenure-track faculty, 2747 undergraduate and 519 graduate students, numerous other staff employees, and generated approximately $16 million in extramural research funding.

The PSS Department is a comprehensive academic unit conducting research and offering coursework and programs in several areas of plant and soil sciences. There are 36 full-time faculty members and a student body consisting of approximately 180 undergraduate and 140 graduate students. B.S., M.S. and Ph.D. level degrees are offered in Plant and Soil Science. Additionally, distance education courses and four certificate programs are offered. The department is research-intensive, while fostering strong teaching expectations and commitments. Students in the department are educated to meet the challenge of using soil, water, and plant resources for sustainable production and environmental quality.

Major/Essential Functions
The Davis College Water Center at Texas Tech University (Lubbock, TX) invites applications for a Post Doc position focused on developing practical digital tools for agricultural water management. The successful candidate will combine knowledge of agriculture and remote sensing with strong coding skills to transform data from field sensors, weather stations, satellites, and crop models into applications that farmers can use to support irrigation and crop-management decisions.

This position offers an opportunity to connect ongoing field and remote-sensing research with farmer-ready products. The Post Doc will work with researchers, extension personnel, producers, and software collaborators to identify user needs; develop, test, and deploy web, mobile, or dashboard applications; and validate recommendations under real farming conditions. The candidate will also contribute to scientific publications, outreach, proposals, and shared project activities.

Work with farmers, crop consultants, and researchers to identify priority management decisions and define requirements for useful, accessible, and scientifically reliable decision-support applications.
Develop reproducible data pipelines and application progrzamming interfaces that integrate soil-moisture sensors, weather and field observations, satellite products, and crop or hydrologic model outputs.
Calibrate, validate, and apply DSSAT crop models using field observations, soil and weather data, irrigation records, crop-management information, and historical datasets from ongoing research and producer-field projects.
Integrate DSSAT simulations with satellite and ground-sensor data to assess crop growth, phenology, soil-water dynamics, evapotranspiration, irrigation requirements, biomass, yield, and crop water productivity.
Apply remote sensing, geospatial analysis, machine learning, and artificial intelligence to map soil moisture, estimate irrigation requirements, classify crops, detect phenology, monitor agricultural drought, and predict biomass or yield.
Connect application development with ongoing small-plot and producer-field research; collect ground-reference data and evaluate model accuracy, uncertainty, limitations, and agronomic usefulness across crops, soils, irrigation systems, and seasons.
Conduct usability testing with farmers and other intended users and improve maps, alerts, interfaces, and recommendations based on user feedback and documented field performance.
Use sound software practices, including version control, code review, automated testing, data-quality checks, privacy safeguards, documentation, and maintainable deployment; prepare peer-reviewed publications, project reports, proposals, training materials, and outreach demonstrations.

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.

This position is designated as involving access to critical infrastructure systems and/or research, as defined by Texas Executive Order GA-48. As such, candidates must successfully complete a comprehensive background check prior to employment. Employees are required to comply with all applicable state and federal regulations related to the protection of critical infrastructure. Ongoing employment is dependent upon maintaining eligibility for access and successfully passing periodic security and compliance reviews.

Preferred Qualifications

Support applications is preferred.
Additional preferred experience includes user-centered design, web or mobile development, cloud platforms, near-real-time sensor integration, machine learning or artificial intelligence, field research, and direct collaboration with farmers, extension programs, producer networks, or agricultural technology partners.
Ph.D. in agricultural or irrigation engineering, agronomy, crop science, soil and water science, remote sensing, geography, computer science, data science, or a related field.
Demonstrated knowledge of agriculture and experience with aerial or satellite remote sensing are required.
Strong programming skills in Python, R, JavaScript, or comparable languages and experience with geospatial data, databases, application programming interfaces, version control, large datasets, quantitative validation, scientific writing, and collaborative research.

Pay Range
$44,500 - $57,900.00 - $71,200

To apply, visit workattexastech.com

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information or status as a protected veteran.