RSS Feed Source: Academic Keys

Job ID: 257301

INESC TEC | Research Initiation Grant (AE2025-0208)
INESC TEC

Research Opportunities

Electrical Engineering

Work description

Study and identification of the main characteristics of INESC TEC’s optimal power flow tool, including all modeled energy resources. Study and modeling of two-stage stochastic programming and robust optimization problems. Adaptation of the tool formulation to stochastic and robust optimization. Implementation of the two-stage stochastic formulation in the existing tool, creating a specific module for its operation. Replication of the previous point for the formulation of the robust OPF. Prepare a scientific report on activities and write scientific articles.

Minimum profile required

Basic knowledge of the optimal power flow problem. Basic knowledge of optimization. Knowledge of the Python programming language. Fluency in English (written and spoken).

Preference factors

Experience

Click this link to continue reading the article on the source website.

RSS Feed Source: Academic Keys

Job ID: 257299

INESC TEC | Research Grant (AE2025-0224)
INESC TEC

Research Opportunities

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

Click this link to continue reading the article on the source website.