Tasks will include: develop machine learning models with high interpretability and the ability for natural language processing; formulate data-based optimization problems (using supervised techniques and reinforcement learning); apply innovative data-drive techniques to use cases related to electricity markets and grid operation under emergency condition; dissemination of work in international journals.

The candidate is required to have a MSc degree in electrical engineering or computer science or similar.

The minimum requirements for the profile are an average grade on the degree and the MSc of 14 out of 20.

Preference will be given to candidates who have: Experience with machine learning models; Advanced knowledge in electrical power systems Knowledge in Python programming Knowledge of metaheuristics for optimization.

Scientific advisor: Ricardo Jorge Bessa.