PhD Student (EDB-IPP Contract)
Core
Conducting research on behaviour-based advanced control algorithms for residential HVAC systems to optimise thermal comfort, enhance occupant wellbeing, and reduce energy consumption.
Role type
PhD Researcher (HVAC Control & AI)
Builds
Behaviour-based control strategies for residential HVAC systems
Domain
Building Technology / Sustainable Energy / AI
Deliverable
research
Required skills
AI and programming, control engineering, data analysis, sensor data integration, deep learning frameworks (PyTorch, TensorFlow), machine learning libraries (scikit-learn), IoT sensor experience, cloud computing platforms
Preferred skills
HVAC system familiarity, modeling techniques, thermal comfort optimization, energy management, published research in reputable venues
Technologies
PyTorch, TensorFlow, scikit-learn, IoT sensors, cloud computing platforms
Responsibilities
Collect and analyse sensor data from real-world residential environments, integrate physiological monitoring data with environmental metrics, design and develop behaviour-based control algorithms, validate control strategies in real-world settings, collaborate with NUS and Bosch research teams
Seniority
PhD Candidate (Researcher)