Computer Science/Informatics
[Closed]
Work description
Adapting the distributed learning method developed by INESC TEC for non-linear regression problems, classification and considering uncertainty. Develop new algorithmic approaches and use cases for data markets. Validate the developed methodologies on real data and different use cases. Dissemination of the work in international journals and/or conferences
Academic Qualifications
Previous academic background in applied mathematics, physics, computer science or similar
Minimum profile required
Previous academic background in applied mathematics, physics, computer science or similar
Preference factors
Experience with time series modelling and forecasting Knowledge in machine learning method Knowledge of programming in Python or R
Application Period
Since 03 Nov 2022 to 03 Dec 2022
[Closed]
Centre
Power and Energy Systems