PhD CIFRE RTE – MINES PARIS: This PhD project aims to improve the predictability of renewable energy generation using advanced AI-based methods. The research will focus on short-term energy forecasting to ensure the economic and secure operation of modern power systems, addressing challenges like extreme weather conditions and non-weather-related factors.
PhD CIFRE RTE – MINES PARIS: Artificial Intelligence for Renewable Energy Forecasting
Designation:
PhD Student (CIFRE Scholarship)
Research Area:
- Artificial Intelligence
- Data Science
- Renewable Energy Forecasting
- Power Systems
- Energy Transition
Location:
Paris, Ile-de-France, France
Eligibility/Qualification:
- Engineer or Master of Science degree (candidates can apply prior to obtaining their master’s degree but must complete it before starting the PhD).
- Strong background in applied mathematics, statistics, data science, machine learning, and artificial intelligence.
- Good analytical, synthesis, innovation, and communication skills.
- Adaptability and creativity, with a coherent professional project.
- Programming skills (e.g., Python).
- Proficiency in French (recommended) and excellent command of English.
Job Description:
The selected candidate will conduct research on advanced AI methodologies to enhance the accuracy of renewable energy generation forecasts across local, regional, and national scales. The PhD project will include:
- Analyzing state-of-the-art forecasting methods.
- Developing novel AI-based forecasting models.
- Evaluating models’ performance using large datasets.
- Integrating additional data sources to improve the forecasting accuracy.
- Ensuring consistency of predictions across different geographical levels.
How to Apply:
Interested candidates should submit their applications through the recruitment portal on the MINES Paris – PSL website. Ensure to include:
- A detailed CV.
- A cover letter expressing motivation and relevant skills.
- Academic transcripts and/or proof of qualifications.
Last Date for Apply:
June 10, 2025
