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Sd-25239 – Phd In Ai Based Energy Forecasting For Energy Communities
Posted on April 1, 2025
- Esch-Sur-Alzette, Luxembourg
- No Salary information.
- Full Time

Temporary contract | 36 months | Belvaux
Are you passionate about research? So are we! Come and join us
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/
How will you contribute?
You will be mainly in charge of:
- Conduct research on AI-based energy prediction and predictive maintenance for EV user charging schedules, balancing user convenience, grid constraints, and renewable energy integration.
- Deploy AI solutions in dedicated cloud-based systems and platforms (e.g. AWS), optimizing architecture and operation.
- Integrate AI solutions with energy management systems (EMS) to optimize interactions between distributed energy resources (DERs) and EV charging infrastructure.
- Collaborate with project partners to test and validate developed AI models in both real-time hardware in loop lab and physical environments.
- Disseminate findings through publications, presentations, and contributions to the EnerTEF project.
Is Your profile described below? Are you our future colleague? Apply now!
Education
- A Master’s degree in electrical engineering, computer science, energy systems, or a related discipline
Experience and skills
- Knowledge on electrical systems operation and markets
- Strong knowledge of AI/ML techniques
- Background on cloud systms deployment and applications (e.g. AWS)
- Proficiency in programming languages such as Python, Pytorch, HyperSim
- Excellent communication skills and the ability to work effectively in a multidisciplinary and collaborative environment.
Language skills
- Good level both written and spoken English
Your LIST benefits
- An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
- Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
- Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
- An environment encouraging curiosity, innovation and entrepreneurship in all areas
- Personalized learning programme to foster our staff’s soft and technical skills
- Multicultural and international work environment with more than 50 nationalities represented in our workforce
- Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
- Gender-friendly environment with multiple actions to attract, develop and retain women in science
- 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
- Flexible working hours, home working policy and access to lunch vouchers
- A dynamic research environment at the forefront of energy systems innovation.
- Access to state-of-the-art facilities, including the ICES RT-HIL simulation laboratory.
- Collaboration opportunities with leading researchers (University of Oxford and Imperial College London) and industry partners in the FlexEdge project and beyond
Apply online
Your application must include:
- A motivation letter oriented towards the position and detailing your experience
- A scientific CV with contact details
- List of publications and patents(if applicable)
- Contact details of 2 references
Please apply ONLINE formally through the HR system. Applications by email will not be considered.
Application procedure and conditions
We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.
Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be the alignment of the applicant's existing skills and expertise with the requirements mentioned above.
PhD additional conditions:
- Supervisor at LIST: Prof. Pedro Rodriguez (pedro.rodriguez@list.lu)
- Work location: Luxembourg Institute of Science and Technology (LIST), Belvaux, Luxembourg
Candidates shall be available for starting their position in 2025. Please note that university enrolment fees (currently 200 EUR per semester) must be covered by the successful applicant. Your master diploma has to be recognized in Luxembourg. Please refer to:
https://www.uni.lu/en/admissions/diploma-recognition/
https://guichet.public.lu/fr/citoyens/enseignement-formation/etudes-superieures/reconnaissance-diplomes.html
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