Why Study Digital Agriculture at UNL?

The Digital Farming Lab at UNL is a leader in using advanced digital agriculture (DA) technologies to improve crop performance and promote sustainable farming. As a Master’s GRA, you’ll contribute to interdisciplinary research that integrates:

• Geographic Information Systems (GIS)
• Crop modeling and production systems
• Remote sensing and vegetation indices
• Big data analytics and field trials

This project is ideal for students passionate about precision agriculture, sustainable crop systems, and digital tools for data-driven farming.

Research Objectives

The selected graduate student will help design and implement research to:

• Optimize nitrogen management strategies
• Improve corn yields using remote sensing and modeling
• Reduce the environmental impact of fertilizers
• Leverage digital technologies to make farming more efficient

Graduate Research Assistant Responsibilities

As part of the research team, you will:

• Conduct and manage field experiments
• Use data analytics, spatial analysis, and modeling tools
• Prepare scientific publications in peer-reviewed journals
• Present findings at national and international conferences

Eligibility Criteria

Applicants must meet the following requirements:

Academic Background:

• Bachelor’s degree in Agronomy, Crop Science, or a closely related field
• Minimum GPA of 3.0 (on a 4.0 scale)

Technical Skills:

• Hands-on experience with GIS, spatial data analysis
• Knowledge of crop modeling and production systems
• Strong skills in field data collection, analysis, and interpretation

Other Requirements:

• Excellent communication and teamwork abilities
• Motivation to work in interdisciplinary agricultural research

International Applicants Welcome

International students are encouraged to apply. English proficiency is required:

• TOEFL: 550 (paper-based) or 79 (internet-based)
• IELTS: Minimum overall band score of 6.5

Financial Support Package

This fully funded Master’s assistantship includes:

• Stipend: $27,876 per year
• Tuition Waiver: Covers up to 12 credit hours per semester and 6–12 credit hours in summer
• Health Insurance: Offered at a reduced cost

Start Date & Application Process

• Start Term: Fall 2025
• Review of Applications: Begins immediately

Step 1: Complete the pre-application form: https://go.unl.edu/digitalgra
Step 2: Upon invitation, submit the full application as instructed by the Digital Farming Lab team.

Contact & Additional Information

University of Nebraska–Lincoln
Department of Agronomy and Horticulture
204 Keim Hall, Lincoln, NE 68583-0915, USA
Email: gbalboa2@unl.edu
Website: https://agronomy.unl.edu

Join a Leading Interdisciplinary Lab in AI, Remote Sensing & Climate Research

Led by Dr. Qian Liu at the School of Natural Resources (SNR), this newly established research group focuses on using AI-powered geospatial analytics to address pressing challenges in environmental monitoring and climate resilience.

This is your chance to work at the intersection of:

• Artificial Intelligence (AI)
• Remote Sensing
• Geospatial Data Science
• Climate and Atmospheric Research

Research Focus Areas

Students in the lab will engage in impactful, data-driven research projects. Core themes include:

• Remote sensing and atmospheric monitoring
• AI-based analytics for climate systems and weather forecasting
• Big data processing for environmental applications
• Spatiotemporal modeling using Earth observation data
• Extreme weather event detection and climate risk mitigation

Who Should Apply?

Ideal candidates should have:

• A background in atmospheric science, remote sensing, computer science, geospatial science, or a related discipline
• Proficiency in programming, data analysis, and/or machine learning
• A strong interest in interdisciplinary research with real-world environmental applications

Program Highlights

Why pursue your PhD or Research Assistantship at the University of Missouri?

• Join a collaborative, fast-growing lab with access to advanced geospatial and AI tools
• Work on real-world environmental challenges with global impact
• Collaborate with experts in machine learning, climate science, and geospatial modeling
• Develop solutions for climate adaptation, natural disaster resilience, and sustainability

Location & Start Date

• Location: University of Missouri, Columbia, Missouri, USA
• Start Date: Fall 2024

How to Apply

To be considered for these positions, please email the following documents to Dr. Qian Liu at qian.liu@missouri.edu:

1. Curriculum Vitae (CV)
2. A brief research statement outlining your interests and goals
3. Contact information of academic references

Don’t Miss This Opportunity

This is a unique opportunity to join a forward-thinking research group at a top U.S. institution. If you’re ready to make a difference in climate and environmental science using AI and remote sensing, apply today!