COMPUTER SCIENCE - Artificial Intelligence

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

Minimum profile required

Previous academic background in applied mathematics or computer science or informatics or electrical engineering or similar

Preference factors

- Past experience (or academic background) with supervised and reinforcement learning

- Academic background in operations research

- Programming knowledge in Python

Application Period

Since 25 Jan 2024 to 24 Feb 2024

Cluster / Centre

Power and Energy / Power and Energy Systems

Scientific Advisor

Ricardo Jorge Bessa