PhD position in physics-informed data-driven techniques for supporting the energy transition of European cities (FPI 2023) per al CIMNE

Functions to be developed:

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 candidate will join the research group of Bee Group: Building, Energy and Environment 

This contract is financed by the announcement of Proyectos de Generación de Conocimiento 2023 of the Ministerio de Ciencia, Innovación y Universidades: Proyectos de Generación de conocimiento 2023| Agencia Estatal de Investigación (aei.gob.es)

The deadline for registration to the offer ends on November 22nd, 2024 at 12 noon.

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