Aalborg University’s Department of Computer Science, within the Technical Faculty of IT and Design, is offering a three-year PhD stipend focused on Cooling Flexibility Modeling, Estimation, Aggregation, and Optimization in the context of sustainable water-based cooling for megacities. The position is part of the Data Engineering, Science, and Systems (DESS) research group, which is internationally recognized for its work in data-intensive systems, spatio-temporal data management, data analytics, and machine learning, particularly in digital energy and intelligent transport. The project is supervised by Professor Torben Bach Pedersen and builds on the award-winning FlexOffer technology, a scalable model for energy flexibility developed at AAU and widely published in top conferences such as ACM e-Energy. The research will address how flexibilities in cooling systems can be leveraged for joint optimization with electricity and cold production, storage, and demand, aiming to minimize both CO2 emissions and costs. The successful candidate will extend FlexOffer technology to model cooling asset flexibilities, estimate flexibility potentials, and develop aggregation and optimization techniques for cold production, storage, and demand. The work will enable co-optimization across energy vectors and provide schedules for trading flexibility with the surrounding energy system. Applicants must have MSc and BSc degrees in Computer Science or Software Engineering, strong software development skills in languages like Rust, C++, or Python, and expertise in algorithms and machine learning. Experience in digital energy, energy flexibility, and FlexOffers is preferred. Excellent English communication skills are required. The position is fully funded according to the Danish AC collective agreement, and the successful candidate will be enrolled in the Technical Doctoral School of IT and Design. Aalborg University is highly ranked globally for engineering and impact, and the Department of Computer Science is known for its leading research and problem-based learning model. Applications must be submitted via the university’s recruitment system and include a statement of motivation, CV, diplomas, and a one-page project description. Diversity is valued, and all qualified candidates are encouraged to apply. Interviews are expected 2-4 weeks after the deadline, and the hiring process includes shortlisting and risk assessment. For further information, contact Professor Torben Bach Pedersen or PhD HR Annemarie Davidsen.