Computer Science
Work description
- Development of model/process chains that enable AI-based assistants to support human operators' decisions in power systems under model risk and uncertainty, and considering joint human-AI learning; - Develop methodologies to assess the robustness and safety of human decisions assisted by AI, hybrid co-learning between AI and humans, and fully autonomous AI, considering risk assessment aligned with the EU AI Act, as well as reliability and robustness quantified through the provision of guidelines on how to create and use “adversarial” datasets; - Validate the developed methodologies using real data and simulators; - Dissemination of the work in national and/or international journals and conferences.
Academic Qualifications
Degree in Computer Science, Informatics of similar area
Minimum profile required
Past experience (or academic training) in Artificial Intelligence, algorithms with a focus on traditional machinelearning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including thedevelopment of data analysis and visualisation pipelines.
Preference factors
- Knowledge of Python programming. - Development of IT tools for use in real environments. - Knowledge of simulation methodologies.
Application Period
Since 22 May 2025 to 05 Jun 2025
Centre
Power and Energy Systems