Artificial Intelligence
[Closed]
Work description
1) Hybridization of physics-based modelling and AI to create decision-support models for human operators under forecast uncertainty. 2) Distributed learning algorithms and coordination strategies to achieve a global goal where, for instance, aspects such as energy consumption (green AI) is covered by testing their implementation in edge devices. 3) Validate the developed methodologies on real data and different use cases focused on energy transition. 4) Dissemination of the work in international journals and/or conferences
Academic Qualifications
PhD degree in: Applied Mathematics; Physics; Computer Science; Electrical and Computer Engineering; Industrial Engineering or similar
Minimum profile required
- Past experience with supervised and reinforcement learning- Python programming skills- A minimum of 2 publications in Q1 journals
Preference factors
Experience in applying reinforcement learning algorithms to engineering problems - Knowledge or experience of energy systems problems
Application Period
Since 25 Jan 2024 to 24 Feb 2024
[Closed]
Centre
Power and Energy Systems