1) Adapting the federated learning method developed by INESC TEC for non-linear regression problems. 2) Developing new algorithmic solutions for data markets. 3) Validate the developed methodologies on real data with thousands of time series. 4) Disseminate the work in international journals and/or conferences.
PhD degree in mathematics, computer science or similar;
Minimum profile required
A minimum of two publications in journals index in Scopus or Web of Science
- Experience with time series modelling and forecasting - Knowledge in machine learning methods - Knowledge of game theory - Knowledge of programming in Python or R
Since 17 Dec 2022 to 15 Jan 2022
Cluster / Centre
Power and Energy / Power and Energy Systems