Fully Funded PhD Scholarship: Controlled Environment Agriculture Technologies – USA
About North Dakota State University
Applications are open for a PhD Controlled Environment Agriculture USA position at North Dakota State University. The research focuses on energy-efficient system operations and water-energy-food system interactions. North Dakota State University (NDSU) is a leading land-grant university located in Fargo, North Dakota, USA. The Department of Agricultural and Biosystems Engineering focuses on innovative solutions for agricultural production, energy efficiency, and sustainable systems. Dr. Iris Feng’s research group specializes in controlled environment agriculture technologies, energy-efficient system operations and modeling, and water-energy-food system interactions.
Scholarship Overview
Project Summary
The successful applicant will join Dr. Iris Feng’s research group to conduct research on controlled environment agriculture technologies, energy-efficient system operations and modeling, and water-energy-food system interactions. The role involves interdisciplinary research, collaboration with multiple stakeholders, and work in both laboratory and field environments.
Why This Scholarship Stands Out
This PhD is unique because it focuses on controlled environment agriculture (CEA) – indoor farming, vertical farms, and greenhouses – which is a rapidly growing sector in the US. The research integrates energy-efficient system modeling with water-energy-food nexus thinking, which is critical for sustainable agriculture. North Dakota State University has strong ties to the agriculture industry, and Fargo offers a low cost of living compared to many US cities. The assistantship provides full tuition coverage plus a competitive stipend, which is renewable annually. For an engineering graduate interested in sustainable agriculture and data-driven modeling, this is an opportunity to develop skills in machine learning, building energy simulation (EnergyPlus), and life cycle assessment – all highly marketable skills.
Candidate Profile and Eligibility
| Requirement | Details |
|---|---|
| Education | B.S. or M.S. in Agricultural Engineering, Environmental Engineering, or closely related field; non-engineering degrees must demonstrate equivalent foundational engineering coursework |
| Minimum GPA | 3.0 cumulative |
| Research Environment | Willingness to conduct research in laboratory and field environments, collaborate with multiple stakeholders |
| Self-Motivation | Strong self-motivation and ability to work independently |
| Communication | Excellent written and verbal communication skills in English |
| English Proficiency | TOEFL iBT 85+ or IELTS 6.5+ for non-English academic credentials |
Preferred Qualifications:
- Experience with interpretable machine learning or data-driven modeling approaches
- Proficiency in at least one programming language (e.g., Python, R)
- Experience with process-based modeling or familiarity with building energy simulation tools such as EnergyPlus
- Background in energy efficiency analysis and life cycle assessment (LCA)
My Application Strategy
- Highlight your engineering background – Agricultural or environmental engineering degrees are preferred. If not, document your foundational engineering coursework
- Emphasize programming skills – Python or R experience is highly valued. Mention specific projects or coursework
- Show interest in controlled environment agriculture – Read about CEA, vertical farming, greenhouses, and energy-efficient systems
- Demonstrate data-driven modeling experience – Machine learning, process-based modeling, or EnergyPlus familiarity is advantageous
- Mention LCA or energy efficiency analysis – Experience with life cycle assessment is a preferred qualification
What They Offer
| Benefit | Details |
|---|---|
| Position | PhD Graduate Research Assistant |
| Funding | Full tuition coverage + competitive stipend |
| Renewal | Annual, based on satisfactory progress |
| Start Date | Fall 2026 or Spring 2027 |
| Location | Fargo, North Dakota, USA |
Who Should Apply
This PhD is perfect for a student with an engineering background (agricultural, environmental, or related) who wants to apply data-driven modeling to controlled environment agriculture. If you are interested in how energy efficiency, water use, and food production intersect – and want to develop skills in machine learning, building energy simulation, and life cycle assessment – this project offers training across these areas. Candidates with programming experience in Python or R are especially encouraged.
How to Apply
Contact Dr. Iris (Xiaoyu) Feng by email with your application materials.
Email: xiaoyu.feng.1@ndsu.edu
Useful Links
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