Currently, there are two full-time Postdoc positions available at the Electrical Energy Systems Group at the Eindhoven University of Technology (TU/e) in the area of electricity markets. The appointments are yearly with the possibility of being extended for a period of up to two years.
The positions are funded by an Education Innovation Fund for the
Development of a competitive serious game for teaching electricity markets. The project aims at developing a web-based multiplayer serious game in order to enhance the teaching of electricity markets subjects. Teaching electricity markets requires the introduction of mathematical theory for dealing with large-scale optimization problems, concepts from various disciplines (e.g., power systems, microeconomics, machine learning, etc.) and programming. This project proposes to actively introduce gamification elements in the teaching and learning process, anticipating the stimulation of student creativity, in parallel to understanding the relevant technical content. Embedding gamification in teaching the subject of electricity markets is expected to contribute to students' development of 21st century skills and to materializing the TU/e vision on education in 2030. More specifically, it will promote research-driven learning within the courses that the developed serious game will be used. In addition to that, digital literacy, problem-solving and creative thinking, as well as team-work, shall become central to the learning process.
The selected candidates are expected to be actively involved in the design, development and evaluation of the game platform, in parallel to conducting academic research in the field of electricity markets. Research topics of interest include (but are not limited to):
- Development of market participation strategies and risk management;
- Market clearing mechanisms under uncertainty;
- Applications of machine learning to electricity markets (e.g., forecasting);
- P2P and local electricity markets;
- Optimization techniques (distributed optimization, decomposition techniques, multi-objective optimization, reinforcement learning etc.).