Energy System Modeling and Data-Driven Techniques
In today's rapidly changing energy landscape, there is an increasing need for advanced modeling techniques to predict and optimize energy system behavior. This research aims to leverage data-driven approaches to enhance the accuracy and efficiency of energy system modeling.
The role involves working on multiple projects, including model development, validation, and data source identification. Strong collaboration skills are essential for success, as interactions with PhD students and participation in research projects are key aspects of this position.
The ESIM research group at KU Leuven's Department of Mechanical Engineering has expertise in modeling energy systems and markets, including unit commitment, system planning, equilibrium modeling, renewables integration, energy policy, and energy market design.
Requirements
* PhD degree in Engineering or a related field from a reputable institute.
* Strong interest in energy system operation and planning, as well as in modeling.
* Experience with Julia/Python/GAMS/Matlab is a plus.
* Good English communication skills.
About the Opportunity
KU Leuven offers a post-doc position for one year, possibly to be extended. Benefits include health insurance and access to university infrastructure and sports facilities.