Algorithms have permeated every aspect of the modern energy system. Increasingly, learning based solutions are replacing existing rule-based and heuristic systems. However, despite their appeal, such systems come with their own challenges ranging from sample inefficiency to poor generalization potential in unseen conditions. The postdoc will support the group’s vision by working closely with a young but brilliant team of PhD researchers to develop cutting-edge algorithms which can address these, and other risks posed by the indiscriminate adoption of algorithms in energy systems.
Additionally, the postdoc will help shape the future of how (and what) energy engineers learn by being involved in a large European project on educational design. This entails making research available to students in a more approachable format (think 3Blue1Brown or Statcraft but for energy). This project will also enable the postdoc to interact with and learn about researchers and professors not just in KU Leuven but also several other top engineering schools in Europe.
The research will be carried out in the ELECTA research group of the Department of Electrical Engineering (ESAT) of KU Leuven, under the supervision of Prof. Hussain Kazmi who heads the research line on energy and data science. Our focus is (1) on developing cutting-edge machine learning algorithms to model and forecast energy demand, generation and markets, and (2) on the control of energy flexible resources to provide grid services.
KU Leuven is among the top European universities, and a key player in the field of energy research.
This research will be performed within the framework of EnergyVille, a research collaboration on sustainable energy between KU Leuven, VITO, Imec, and UHasselt.
Energy • Leuven, BE