Research Opportunity
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
Academic Qualifications
PhD degree in: Applied Mathematics; Physics; Computer Science; Electrical and Computer Engineering; Industrial Engineering or similar
Minimum profile required
- Past experience with supervised and reinforcement learning;
- Python programming skills;
- A minimum of 2 publications in Q1 journals
Preference factors
- Experience in applying reinforcement learning algorithms to engineering problems
- Knowledge or experience of energy systems problems
Maintenance stipend: € 1801,00, according to the table of monthly maintenance stipend for FCT grants , paid via bank transfer. Grant holders may be awarded potential supplements, according to a quarterly evaluation process (Articles 19, 21 and 22 of the Regulations for Grants of INESC TEC and Annex II), up to a maximum limit of 50% of the monthly maintenance stipend.
Application Period
Since 29 Apr 2024 to 29 May 2024
Centre
Power and Energy Systems
Scientific Advisor
Ricardo Jorge Bessa
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