SD-25089 – POSTDOC IN AI BASED ENERGY MANAGEMENT FOR ENERGY COMMUNITIES

Temporary contract | 24 months | Belvaux Are you passionate about research? So are we! Come and join us

How will you contribute?

You will be mainly in charge of:

• Working with real-time simulators (OPAL-RT) with hardware in the loop functionalities to test and validate AI-based solutions in complex operation environments
• Working with rapid prototyping tools (dSPACE) to recreate charging profiles and communication protocols of electrical vehicles
• Working with IoT, meters, controllers, IED, etc to manage real-time data from the edge-level to be used as inputs for AI-models
• Integrate AI solutions with energy management systems (EMS) to optimize interactions between distributed energy resources (DERs) and EV charging infrastructure.
• Disseminate findings through publications, presentations, and contributions to the EnerTEF project.

The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

You will join the Intelligent and Clean Energy Systems (ICES) research unit at the Luxembourg Institute of Science and Technology (LIST) and will actively contribute to the EnerTEF project, funded by the Horizon Europe, in collaboration with research institutes and Industrial partners around Europe.

EnerTEF focus on establishing a Common Federated AI Testing and Experimentation Facility (TEF) for the energy field. Specifically, it leverages AI and cutting-edge infrastructure to optimize EV charging and energy systems. By integrating distributed energy resources, demand response, and storage, it aims to enhance grid flexibility and renewable energy use. Through advanced analytics and digital twin environments, EnerTEF delivers innovative solutions for the local energy community.

Do you want to know more about LIST? Check our website: https://www.list.lu/

Is Your profile described below? Are you our future colleague? Apply now!

Education

• A PhD’s degree in electrical engineering, computer science, energy systems, or a related discipline.

Experience and skills

• Hands-on experience with RT-HIL and rapid prototyping (dSPACE and OPAL-RT)
• Background in communication networks and protocols
• Familiar with networked controllers and meters
• Proficiency in programming languages such as Python, Pytorch, HyperSim.
• Background in AI techniques and tools
• Excellent communication skills and the ability to work effectively in a multidisciplinary and collaborative environment.

Language skills

• Good level both written and spoken English