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Crop Modeling Jobs in Washington (NOW HIRING)

Crop Modeling information

What are the typical daily responsibilities of someone working in Crop Modeling?

Professionals in Crop Modeling typically spend their days designing and running simulations, analyzing data from field trials or remote sensing, and refining models to predict crop growth under various environmental conditions. Collaborating with agronomists, data scientists, and farmers is common to ensure models reflect real-world variables and are practical for field application. Additionally, they may present findings through reports or presentations, participate in multidisciplinary research projects, and stay updated on advancements in agricultural technology. This variety ensures each day offers unique challenges and opportunities to impact agricultural outcomes.

What are the key skills and qualifications needed to thrive in the Crop Modeling position, and why are they important?

To thrive in Crop Modeling, you need a solid background in agricultural science, data analysis, and mathematical modeling, often requiring an advanced degree in agronomy, environmental science, or a related field. Familiarity with crop simulation software (like DSSAT or APSIM), programming languages such as Python or R, and GIS tools is commonly expected. Strong problem-solving skills, attention to detail, and effective collaboration are key soft skills that enhance performance in this role. These skills are crucial for developing reliable models that inform decision-making in agriculture and support sustainable crop management practices.

What is a Crop Modeling job?

A Crop Modeling job involves developing and using computer-based models to simulate plant growth, yield, and environmental interactions. Professionals in this field analyze data related to weather, soil, and crop management to predict agricultural outcomes and optimize farming practices. They work closely with agronomists, researchers, and policymakers to improve food production efficiency and sustainability. This role typically requires expertise in agronomy, data science, and programming.

Infographic showing various Crop Modeling job openings in Washington as of July 2026, with employment types broken down into 80% Full Time, 12% Part Time, 3% Temporary, and 5% Contract. Highlights an 85% In-person, 4% Hybrid, and 11% Remote job distribution.
Research Assistant Professor

Research Assistant Professor

George Mason University

Fairfax, VA • On-site

Other

Posted 20 days ago


George Mason University rating

8.3

Company rating: 8.3 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

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Job description

Research Assistant Professor
  • 10003688
  • Research Faculty
  • Opening on: Jan 26 2026
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Department: College of Science

Classification: 12-month Research Faculty

Job Category: Research Faculty

Job Type: Full-Time

Work Schedule: Full-time (1.0 FTE, 40 hrs/wk)

Location: Remote

Workplace Type: Remote Eligible

Sponsorship Eligibility: Eligible for visa sponsorship

Salary: Salary commensurate with education and experience

Restricted: Yes

Criminal Background Check: Yes

About the Department:

The Center for Spatial Information Science and Systems (CSISS) is an interdisciplinary research center affiliated with the College of Science at George Mason University. The mission of the Center is to conduct world-class research in spatial information science and system and provide state-of-art research training to post-doctoral fellows, Ph.D. and Master students in the field. For more information about the center, please visit http://csiss.gmu.edu/.
George Mason University College of Science (Mason Science) is committed to advancing inclusive excellence and fostering an environment free from discrimination, harassment, and retaliation throughout our STEM community. At Mason Science, our values include cultivating an organizational culture that promotes belonging, respect, and civility. We believe that varied opinions, cultures, and perspectives are what provides vibrancy, innovation, and growth to an academic community. By prioritizing cultural responsiveness in academics, teaching, research, and global engagement, we strive to attract faculty and staff who exemplify the Mason Science mission and vision.

About the Position:

This position is funded by a USDA-funded research project. The primary purpose of the position is to monitor the conditions of crop, pasture, and their growth environment to support agricultural decision making with advanced remote sensing and geospatial technologies.

Responsibilities:

  • Develops advanced Agro-geoinformatic algorithms for monitoring and predicting the conditions of crop, pasture, and their environment with advanced remote sensing and geospatial technologies;
  • Develops and refines algorithms and workflows for crop and pasture monitoring, modeling, prediction, and decision support and automation;
  • Supervises graduate research assistants and student interns working on the project; and
  • Publishes and disseminates research at top-tier journals and conferences.

Required Qualifications:

  • Terminal degree in a related field;
  • One-year post-Ph.D. research experience in related field at the time of appointment;
  • Research experience in agricultural remote sensing, crop and pasture modeling, or agricultural environment monitoring and prediction;
  • Knowledge of remote sensing, geospatial information systems, crop modeling and prediction, Agro-AI/ML, or agricultural digital twin; and
  • Knowledge of relevant programming skills.

Preferred Qualifications:

  • At least two-years post-Ph.D. research experience in related fields;
  • Track record that demonstrates the ability to work well with an interdisciplinary research team;
  • Excellent publication records;
  • Experience in large-scale earth observation analytics;
  • Experience in integrating multi-source remote sensing data with process-based or data-driven models to characterize agricultural and ecological systems;
  • Experience in applying advanced Artificial Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and
  • Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin.

Instructions to Applicants:

For full consideration, applicants must apply for the Research Assistant Professor at https://jobs.gmu.edu/. Complete and submit the online application to include three professional references with contact information, and provide a cover letter and CV for review.

Posting Open Date: January 26, 2026

For Full Consideration, Apply by: February 9, 2026

Open Until Filled: Yes


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