Ph.D. Position

**Job Description**
This Ph.D. position, part of the LEAP-AI project, addresses challenges in autonomous greenhouse control to ensure sustainable, affordable, and reliable local food production. The project aims to design the next generation of autonomous greenhouse control systems by integrating formal methods from computer science (program synthesis and probabilistic programming) with control systems analysis. The role involves deriving human-understandable strategies from data-driven AI techniques, connecting short-term actions to long-term effects, and explaining these insights to growers to improve system flexibility and explainability. The successful candidate will collaborate with other Ph.D.s, researchers, and industrial partners specialized in machine learning, climate control, and computer vision for high-tech greenhouses.

**Skills & Abilities**
• Strong background or interest in formal methods in computer science (program synthesis, probabilistic programming), systems and control, machine learning, and biological systems.
• Experience conducting, designing, and/or managing experiments for physical/biological systems (a plus, but not required).

**Qualifications**
Required Degree(s) in:
• Computer Science
• Systems and Control
• Engineering
• Applied Mathematics
• Related field

Other:
• Completed (or in the process of completion) a relevant MSc degree.
• English proficiency at a certain level.

**Experience**
Other:
• Some experience conducting, designing, and/or managing experiments for physical/biological systems is a plus, but not required.

Note: We’ve analyzed the actual job post using AI, for more details visit the original job post by clicking on “Apply Now”!