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Remote Crop Modeling Jobs in Oklahoma (NOW HIRING)

Remote Crop Modeling information

What is remote crop modeling?

Remote crop modeling is the use of computer simulations and remote sensing technologies, such as satellite imagery and drones, to predict and monitor crop growth, yield, and health from a distance. This approach combines data from various sources, including weather, soil, and plant characteristics, to create accurate models of crop performance. Remote crop modeling helps farmers and agronomists make informed decisions about irrigation, fertilization, and pest control, ultimately improving productivity and sustainability. It is widely used in precision agriculture to optimize resource use and reduce environmental impact.

What are the key skills and qualifications needed to thrive in remote crop modeling?

To thrive in Remote Crop Modeling, you need a strong background in agronomy, data analysis, and environmental science, often supported by a relevant degree such as agricultural engineering or crop science. Familiarity with crop modeling software (e.g., DSSAT, APSIM), remote sensing tools, and programming languages like Python or R is essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret data and collaborate with multidisciplinary teams. These competencies ensure accurate crop predictions, informed decision-making, and the successful application of modeling insights to real-world agricultural challenges.

What are the main challenges faced by professionals working in remote crop modeling, and how can they be overcome?

Professionals in remote crop modeling often face challenges related to integrating large datasets from various sources, such as satellite imagery, weather stations, and soil sensors. Ensuring data quality and model accuracy while working remotely requires strong data management skills and effective collaboration with agronomists, data scientists, and software engineers. Regular communication and use of collaborative platforms are essential to align project goals and share updates. Additionally, staying current with the latest modeling techniques and remote sensing technologies can help overcome technical challenges and improve predictive outcomes.

What are popular job titles related to Remote Crop Modeling jobs in Oklahoma?

For Remote Crop Modeling jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Remote Crop Modeling jobs in Oklahoma look for?

The top searched job categories for Remote Crop Modeling jobs in Oklahoma are:

What cities in Oklahoma are hiring for Remote Crop Modeling jobs?

Cities in Oklahoma with the most Remote Crop Modeling job openings:

Infographic showing various Remote Crop Modeling job openings in Oklahoma as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Postdoctoral Researcher AF7795

Oklahoma State University

Stillwater, OK • On-site, Remote

$108K/yr

Full-time

Re-posted 28 days ago


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Job description

Postdoctoral Researcher AF7795

Apply now Job no: 494324
Work type: Adjunct/Temp Faculty
Location: Stillwater
Categories: Research

Campus

OSU-Stillwater

Contact Name & Email

Dr. Yuting Zhou, yuting.zhou@okstate.edu

Work Schedule

TBD

Appointment Length

12 months or less

Hiring Range

Commensurate with education and experience

Priority Application Date

While applications will be accepted until a successful candidate has been hired, interested parties are encouraged to submit their materials by May 20, 2026, to ensure full consideration.

Special Instructions to Applicants

Interested applicants should submit:
1) Cover Letter: a one-page summary of research expertise specifically related to the project
2) a detailed Curriculum Vitae (CV) including educational background, research experience, publications, and contact information for three or more professional references
Questions about this position can be directed to Dr. Yuting Zhou (yuting.zhou@okstate.edu) and Dr. Pradeep Wagle (pradeep.wagle@usda.gov).

About this Position

For a collaborative project between Oklahoma and Central Plains Agricultural Research Center (OCPARC) at the USDA-ARS, El Reno, OK (https://www.ars.usda.gov/plains-area/el-reno-ok/ocparc/) and the Department of Geography at Oklahoma State University (https://cas.okstate.edu/geography/), we are seeking a motivated Post-doctoral Researcher. This role focuses on quantifying the complex interactions between management practices, cropping systems, and weather variability on carbon and water cycles across diverse agroecosystems, including native prairie and tame pastures, winter wheat, alfalfa, and different summer cash or cover crops.

Responsibilities:

The successful candidate will hold a 100% research appointment and will be located at the USDA-ARS, El Reno, OK. The candidate will also work with collaborative teams at the University of Oklahoma. By synthesizing eddy flux data from an unparalleled network of 17 eddy covariance (EC) towers at the USDA-ARS, El Reno, OK with multi-source satellite remote sensing (e.g., Landsat, Sentinel, and CubeSats), high-resolution UAV imagery, and site-specific meteorological records, the researcher will evaluate resource use efficiency in various agroecosystems, specifically light, carbon, and water use efficiency, under varying land-use intensities (e.g., burning, grazing, and till vs. no-till, irrigated vs. rainfed). The researcher will contribute to the development of predictive agroecosystem models designed to optimize agricultural productivity while enhancing environmental resilience. The successful candidate will be jointly supervised by Dr. Yuting Zhou (Oklahoma State University) and Dr. Pradeep Wagle (USDA-ARS).

Salary and benefits:

Salary will be commensurate with education, experience, and qualifications, and is contingent on available funding. Benefits include comprehensive medical plans. Information on benefits can be found at https://hr.okstate.edu/benefits/index.html.

Employment conditions:

This is a full-time (100%), 12-month temporary research, non-tenure track position. An extension for a second year is possible, contingent upon the successful performance of the candidate and available funding. Ideal start date is June 1, 2026.

About OSU:

Oklahoma State University is a Carnegie Tier-1 university with excellent research facilities. Oklahoma State University is located in Stillwater, OK, rated as the friendliest college town in the U.S. Because of its mid-continent location that spans a broad expanse of habitats, Oklahoma has both prairie and forest ecosystems that support an exceptional level of biodiversity.

Required Qualifications
  • Ph.D. degree (at the time of appointment) in biometeorology, geography, ecology, agronomy, remote sensing, or a closely related field.
    (degree must be conferred on or before agreed upon start date)
  • Familiarity with field measurements, field sampling, and high-performance computing environments.

  • Skills, Proficiencies, and/or Knowledge:
    • Strong programming and statistical skills (e.g., R, Python, MATLAB) for handling large, complex eddy fluxes, meteorological records, and remote sensing data.
    • Proven ability to work both independently and in a collaborative, multi-disciplinary setting.
    • Excellent written and oral communication skills, evidenced by first-author peer-reviewed publications in reputed journals.  

Advertised: 08 May 2026 Central Daylight Time
Applications close:

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