PhD Stipend in Anomaly Detection for Future Urban Cooling Systems (Electrical and Electronic Engineering)
The Department of Electronic Systems at Aalborg University invites applications for a three-year PhD stipend in Anomaly Detection for Future Urban Cooling Systems, starting September 1, 2026 or as soon as possible thereafter. This position is part of the Electrical and Electronic Engineering study programme and is embedded within the SWiM project, an international collaboration involving Aalborg University, Aarhus University, Nanyang Technological University, and Grundfos company.
Aalborg University is renowned for its high academic quality and societal impact, particularly in electronic engineering. The Department of Electronic Systems employs over 200 staff, including about 90 PhD students, and is highly international. The department conducts world-leading research in communication, networks, control systems, AI, sound, cyber security, and robotics, leveraging unique research infrastructure and lab facilities. It actively collaborates with industrial partners to transfer research results into real-world applications.
This PhD project addresses the challenge of intelligent, automated monitoring and management of large-scale cooling systems in urban environments. As cities expand and urban heat intensifies, efficient and reliable cooling infrastructure becomes critical. Current systems face issues such as design oversizing, poor maintenance, and inadequate commissioning, leading to inefficiency and energy waste. Early detection and diagnosis of faults at the component, building, and city-district level are essential for sustainable urban development.
The research objectives include two main directions: continuous commissioning and adaptive control, and anomaly detection and fault diagnosis. The candidate will develop methods for ongoing, automated adjustment of controllers, sensors, actuators, and control hardware, using reinforcement learning as a primary methodology. The project also involves creating a multi-level diagnostic framework that integrates physics-informed and data-driven AI methods for efficiency monitoring and fault detection, as well as statistical anomaly detection to identify deviations from normal operation.
The PhD Fellow will be affiliated with the Learning and Decisions research group, which focuses on enabling machines and infrastructures to operate autonomously and collaborate with people. The group develops AI methods to make infrastructures and production more effective and energy-efficient, with a strong emphasis on safety and optimal decision-making.
Applicants must hold a Master's degree in electrical engineering, control engineering, applied mathematics, computer science, or a related field. A strong background in probability and statistics, machine learning, or control theory is required, along with good programming skills (Python, MATLAB, or similar) and excellent English communication skills. Enrollment as a PhD student at the Technical Doctoral School of IT and Design is mandatory, and candidates must complete PhD courses (30 ECTS), gain teaching or knowledge dissemination experience, and undertake an external research stay (3-6 months).
Salary and terms of employment follow the collective agreement between the Danish Confederation of Professional Associations and the state. The application must be submitted via Aalborg University’s recruitment system, including a motivation statement, CV, diplomas, and a research vision. The university values diversity and encourages applications from all backgrounds. Shortlisting will be applied, and all applicants will be informed of their status.
For further information, contact Professor Rafal Wisniewski ([email protected]) or Lisbeth Diinhoff ([email protected]).
