Computer Science
Work description
Development and application of artificial intelligence, machine learning, and statistical methods for time-series forecasting in the electricity sector, including demand, renewable generation, and market prices. Development and evaluation of point and probabilistic forecasting models, including uncertainty quantification. Automation of forecasting processes, covering data preparation, model training and updating, forecast generation, performance monitoring, and systematic evaluation of results.
Academic Qualifications
Master’s degree in applied mathematics, physics, computer science, electrical and computer engineering or informatics or similar.
Minimum profile required
Basic knowledge about machine learning. Programming skills in Python.
Preference factors
Experience in the development and application of machine learning algorithms to engineering problems; - Proven experience in the development of Python libraries and tools; - Experience with software version control tools, preferably Git; - Fluency in English, both written and spoken.
Application Period
Since 18 Sep 2026 to 17 Oct 2026
Centre
Power and Energy Systems
Scientific Advisor
José Ricardo Andrade