**Job Description**
This PhD project, a collaboration between the Technical University of Denmark (DTU) and Chalmers University of Technology, aims to enhance building energy flexibility through advanced data-driven energy management techniques. The focus is on identifying promising Reinforcement Learning-Model Predictive Control (RL-MPC) strategies for real-life building management settings and upscaling their application. The project integrates and advances the disciplines of energy technology, building physics, HVAC systems, computer science, and control systems architecture. The PhD candidate will contribute to the SEEDS research and innovation project and the IEA EBC Annex 96 global expert network.
**Skills & Abilities**
• Knowledge of building physics and HVAC system
• Experience in advanced controls (e.g., RL, MPC)
• Programming knowledge (e.g., Python, R, MATLAB)
• Experience in built environment monitoring
• Fluent English skills, both written and spoken
• Ability to publish research results in high-reputation international journals
• Confidence in working independently and in teams
• Ability and willingness to work in inter- and transdisciplinary teams
• Critical thinking
**Qualifications**
You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree.
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