Summary
Delft University of Technology (TU Delft) is offering a PhD position on Learning and Control for Complex Large-Scale Systems with Applications in Greenhouses. The project is part of the GreenControl initiative, which aims to develop autonomous, crop-centric greenhouse control strategies to support climate-neutral Controlled Environment Agriculture (CEA). The research targets 25% energy savings and 35% reduction in energy costs through advanced sensing, modelling, learning, and control.
PhD Scholarship/Position: Learning and Control for Complex Large-Scale Systems with Applications in Greenhouses
Designation
PhD Researcher / Doctoral Candidate
Research Area
- Systems and Control
- Applied Mathematics
- Machine Learning
- Learning Theory
- Controlled Partial Differential Equations (PDEs)
- Koopman Operators
- Neural Networks
- Data-Driven Predictive Control
- Greenhouse Automation and Controlled Environment Agriculture
- Microclimate Sensing and Modelling
- Energy-Efficient Agricultural Systems
Location
Delft, Netherlands
Faculty of Mechanical Engineering, TU Delft.
Eligibility / Qualification
Applicants should have:
- A completed MSc degree in Systems and Control, Applied Mathematics, Engineering, or a related field.
- A strong background or interest in systems and control, applied mathematics, machine learning, and biological-system applications.
- Experience with conducting, designing, and/or managing experiments involving physical or biological systems is preferred but not mandatory.
- English proficiency sufficient for doctoral education, scientific writing, and communication.
Job Description
The PhD researcher will develop learning and control methods for complex, large-scale greenhouse systems. The research will move beyond conventional average-climate control toward direct crop-centric control, using microclimate sensing, crop modelling, and data-driven approaches.
Key research activities include:
- Developing reduced-order, hybrid and transferable models for airflow, CO₂ concentration, temperature, and humidity.
- Investigating optimal sensor and actuator placement.
- Developing hybrid data-driven and model-based control algorithms.
- Designing predictive control approaches using Koopman operators and/or SINDy.
- Optimizing ventilation, heating, artificial lighting, CO₂ dosing, and screens while considering energy-price fluctuations.
- Conducting high-fidelity numerical simulations followed by validation on a greenhouse demonstrator.
- Exploring the intersection of learning theory, PDEs, systems and control, potentially using RKHSs, Koopman operators, and neural networks.
The position is part of a multidisciplinary consortium involving TU Delft, Wageningen University, University of Twente, TU Eindhoven, and industrial partners working in greenhouse technology, plant breeding, sensing, monitoring, software, and climate control.
Scholarship / Salary & Benefits
- 4-year PhD employment, normally divided into an initial 1.5-year contract and a subsequent 2.5-year contract subject to satisfactory progress.
- Salary: €3,059–€3,881 gross/month, increasing from the first to fourth year for a full-time 38-hour/week contract.
- 8% holiday allowance
- 8.3% end-of-year bonus
- TU Delft Graduate School enrollment and doctoral education.
- Customisable compensation package and health-insurance discounts.
- Monthly work-cost contribution.
- Flexible work arrangements.
- Relocation support through TU Delft’s Coming to Delft Service.
How to Apply
Apply online through the TU Delft vacancy application link. Email or postal applications will not be processed. Applicants should upload:
- CV including education and relevant work experience.
- Motivation letter of no more than one page explaining interest in the research topic, motivation for pursuing a PhD, and suitability for the position.
- One or two research-oriented documents, such as an MSc thesis or journal/conference publication.
- BSc and MSc transcripts, including course grades.
- If shortlisted for interview, contact details of two referees will be requested with their consent.
Contact:
Prof. Dr. Ir. Tamas Keviczky — t.keviczky@tudelft.nl
Dr. Mohammad Khosravi — mohammad.khosravi@tudelft.nl
Last Date to Apply
30 September 2026
