Postdoctoral Fellow in Cropping Systems, Data Science & Agricultural Modelling at the University of Missouri, USA (2026)
This two-year postdoctoral fellowship offers an exciting opportunity for researchers interested in agronomy, crop physiology, agroecology, agricultural data science, machine learning, and process-based modelling. The position focuses on understanding how interactions between genotype, environment, and management (G×E×M) influence crop productivity, sustainability, and resilience.
Applications are open until 30 June 2026.
About the Position
Modern agriculture faces increasing challenges from climate variability, changing management practices, and the need to sustainably intensify crop production.
This postdoctoral project aims to identify strategies that:
Minimize crop stress
Increase productivity
Improve farm profitability
Enhance environmental sustainability
Support climate-resilient agricultural systems
The successful researcher will work with extensive datasets collected from multiple field experiments conducted across Missouri during the past five years and from ongoing research projects.
Research Areas
The project focuses on four major research themes.
1. Productivity and Economics of Intensified Crop Rotations
Investigating how different crop rotation systems affect:
Crop productivity
Farm profitability
Resource-use efficiency
Environmental sustainability
2. Crop Management Based on Phenology
Studying how crop developmental stages can guide management decisions such as:
Planting
Irrigation
Fertilization
Harvest timing
3. Physiological Responses to Late-Season Stress
Understanding how crops respond to:
Heat stress
Drought stress
Nutrient limitations
Other environmental stressors
4. Double-Crop Systems
Evaluating the feasibility and performance of double-cropping systems and their potential contribution to sustainable intensification.
Research Methods
The fellowship combines:
Field Experimentation
Crop production trials
Agronomic field studies
Multi-location experiments
Statistical Analysis
Regression modelling
Data synthesis
Advanced statistical methods
Machine Learning
Predictive modelling
Data-driven decision support
Agricultural analytics
Process-Based Crop Modelling
The researcher may work with models such as:
DSSAT (Decision Support System for Agrotechnology Transfer)
APSIM (Agricultural Production Systems Simulator)
Expected Outputs
During the two-year appointment, the fellow is expected to:
Publish four scientific papers
Have three papers accepted in peer-reviewed journals
Submit at least one additional manuscript
In addition, the fellow will prepare:
Extension materials
Farmer-oriented publications
Outreach resources for agribusiness stakeholders
Candidate Requirements
Applicants should possess:
Essential Qualification
PhD in:
Agronomy
Agroecology
Ecology
Soil Science
Natural Resources
Environmental Science
Agricultural Engineering
Statistics
Data Science
Or a related discipline
The PhD must be completed by the time of appointment.
Required Skills
Successful candidates should demonstrate:
Excellent written and oral communication skills in English
Ability to work independently and collaboratively
Strong understanding of agricultural systems
Knowledge of plant-soil-environment interactions
Desired Technical Expertise
Experience in several of the following areas is advantageous:
Data processing
Statistical analysis
R programming
Regression models
Machine learning
Bayesian statistics
Geospatial analysis
Crop modelling
DSSAT
APSIM
The University emphasizes that candidates are not expected to be experts in every area. Researchers with strong quantitative skills and a willingness to learn are strongly encouraged to apply.
Research Environment
The successful candidate will work within:
University of Missouri Plant Science Department
in collaboration with:
USDA-ARS Cropping Systems and Water Quality Research Unit
This collaboration provides access to:
Extensive field datasets
Interdisciplinary expertise
Applied agricultural research
Strong extension networks
About the University of Missouri
Founded in 1839, the University of Missouri (Mizzou) is one of the leading public research universities in the United States.
The university is recognized for excellence in:
Agriculture
Plant Sciences
Environmental Research
Data Science
Extension and Outreach
The university maintains strong partnerships with federal agencies, including the USDA, enabling researchers to conduct impactful applied research.
Position Details
Position Title: Postdoctoral Fellow
Institution: University of Missouri
Location: Columbia, Missouri, USA
Duration: 2 Years
Employment Type: Full-time
Earliest Start Date: Candidates should ideally be available to begin within three months.
Salary and Benefits
The position includes:
Competitive postdoctoral salary
Medical insurance
Dental insurance
Vision insurance
Retirement benefits
Educational fee discounts
Comprehensive university employee benefits
Visa Sponsorship Information
Important
Applicants must already be authorized to work in the United States.
The University of Missouri will not sponsor employment visas for this position.
This means international applicants requiring visa sponsorship are unfortunately not eligible unless they already possess valid U.S. work authorization.
Application Documents
Applicants should submit a single PDF file containing:
Letter of Interest
Curriculum Vitae (CV)
Contact information for three professional references
Applications must be submitted online through the University of Missouri employment portal.
Important Dates
Application Deadline: 30 June 2026 (Midnight CST)
Position Type: Fully Funded Postdoctoral Fellowship
Duration: 2 Years
Location: Columbia, Missouri, USA
Official Application Link
Frequently Asked Questions (FAQ)
1. What is the main focus of this postdoctoral fellowship?
The project focuses on cropping systems research, agricultural modelling, machine learning, and sustainable crop production strategies.
2. Which disciplines are eligible?
Researchers with PhDs in agronomy, agroecology, ecology, soil science, environmental science, agricultural engineering, statistics, data science, and related fields are encouraged to apply.
3. Is machine learning experience required?
Machine learning experience is highly desirable but not mandatory. Strong quantitative skills and the ability to learn are equally important.
4. Which crop models are used?
The project may involve:
DSSAT
APSIM
Other process-based crop models
5. Is this position fully funded?
Yes. The position is fully funded for two years and includes university employee benefits.
6. Are international applicants eligible?
Only applicants already authorized to work in the United States are eligible because visa sponsorship is not available.
7. What publications are expected?
The fellow is expected to:
Publish three accepted papers
Submit one additional manuscript
during the two-year appointment.
8. Is programming experience required?
Experience with R, statistical modelling, and data analysis is highly desirable.
9. Does the position involve outreach activities?
Yes. The fellow will also prepare extension materials and communicate findings to farmers and agribusiness stakeholders.
10. When is the application deadline?
Applications must be submitted by 30 June 2026.
Final Thoughts
The Postdoctoral Fellow in Cropping Systems, Data Science & Agricultural Modelling at the University of Missouri offers an outstanding opportunity for researchers interested in sustainable agriculture, crop modelling, machine learning, and agronomic innovation. Through collaboration with the USDA-ARS and access to extensive long-term datasets, the successful candidate will contribute to impactful research that addresses some of the most pressing challenges facing modern agriculture.
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