Computer Science - Informatics
[Closed]
Work description
1) Adapting the distributed learning method developed by INESC TEC for non-linear regression problems, classification and considering uncertainty. 2) Develop new algorithmic approaches and use cases for data markets. 3) Validate the developed methodologies on real data and different use cases. 4) Dissemination of the work in international journals and/or conferences
Academic Qualifications
PhD degree in computer science, mathematics or similar.
Minimum profile required
A minimum of two publications in journals or international conferences.
Preference factors
Experience with time series modelling and forecasting; Knowledge in machine learning methods; Knowledge of programming in Python or R.
Application Period
Since 31 Aug 2022 to 13 Sep 2022
[Closed]
Centre
Power and Energy Systems