A doctoral thesis in the framework of the research project entitled OMELET: Advanced semantic knowledge graph methods for the massive integration of renewables and storage in electrical distribution networks at the district level, with reference PID2023-152461OB-I00. Principal investigators: Prof. Jordi Cipriano Lindez and Prof. Stoyan Viktorov Danov.
To develop and implement physics-informed machine learning algorithms to analyse and interpret complex data from cities and energy communities. Collaborate with other researchers to develop computational models integrating physical principles with data-driven approaches. Conduct research to advance the field of physics-informed data-driven methods, including developing new algorithms and techniques. Contribute to scientific publications and presentations to disseminate findings and advancements in the field.
Additional information about the project is available at: CIMNE RTD Project: OMELET
The deadline for registration to the offer ends on February 13th, 2025 at 12 noon.
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