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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