PhD in Learning-Based Control for Greenhouse Microclimates

Delft; Netherlands; On-site; EUR 34,000 - 43,000; Full time

Job summary

TU Delft invites applications for a PhD position on Learning and Control for Complex Large-Scale Systems with applications in greenhouses. The project spans GreenControl consortium across TU Delft, Wageningen University, and partners, aiming at climate-neutral CEA with data-driven control strategies.

The PhD will develop learning-based, model-predictive control methods using microclimate sensing and Koopman operators to optimize lighting, CO2 dosing, and ventilation while reducing energy use.

Qualifications

• Completed MSc degree in systems and control, applied mathematics, engineering, or related field.
• Strong background in systems and control, applied mathematics, machine learning, and affinity with biological systems applications.
• Some experience conducting, designing, and / or managing experiments for physical / biological systems is preferred, but not required.

Responsibilities

• Develop learning and control methods for complex large-scale greenhouse systems.
• Perform reduced-order model learning of airflow dynamics, CO2 level, temperature, humidity.
• Design and evaluate learning-based control policies with sensor data and CFD data.
• Collaborate with consortium partners and run validation experiments.

Skills

Systems & control

Applied mathematics

Machine learning

Interdisciplinary

Education

MSc degree in systems and control, applied mathematics, engineering, or related field

Job description

TU Delft invites applications for a PhD position on Learning and Control for Complex Large-Scale Systems with applications in greenhouses. The project spans GreenControl consortium across TU Delft, Wageningen University, and partners, aiming at climate-neutral CEA with data-driven control strategies.

The PhD will develop learning-based, model-predictive control methods using microclimate sensing and Koopman operators to optimize lighting, CO2 dosing, and ventilation while reducing energy use.