As part of its ambition to achieve net zero by 2050, TotalEnergies is building a portfolio of renewable energies and electricity businesses. TotalEnergies will continue to develop this activity to reach 100 GW of gross production capacity from renewable sources by 2030, with the goal of being among the world's top 5 wind and solar power producers. In this context, we have an internship opportunity at the Integrated Power Modeling (IPM) Team at Palaiseau. You will collaborate within an interdisciplinary team and present results at scientific meetings and conferences. The internship can also potentially lead to a publication in a peer-reviewed scientific journal.

As a Wind Data Analysis and Optimization Intern (M/F), your responsibilities will include:

This internship will focus on the analysis and optimization of real wind farm data. Wind data can be analyzed from two complementary perspectives: the time-series approach and the statistical approach. You will investigate the relationships between these two representations, with the following objectives.

1) Characterizing temporal and spatial variability of wind parameters such as wind direction and wind speed. These studies will help understand the importance of time series VS statistical wind data.

2) Quantifying the loss of accuracy or information when transitioning from time-series to statistical data.
Sensitivity analyzes will be conducted on WIFAS-AEP, an internal tool used to simulate wind farms.

3) Exploring strategies to reduce time-series complexity while achieving comparable modeling precision. Explored strategies can go from simple heuristics to more complex machine learning-based systems.

Impact

The different analyses conducted in the internship will help researchers and technical developers better understand the wind data on which every project relies.
And especially, the relationship between the wind data, its format (statistical VS time series) and wind farm simulation.

The strategies you will develop to reduce time-series complexity will have a direct impact on other wind farm optimization projects.
You will work on real wind farm projects and you will potentially gather your results and your findings into a scientific publication.

You will work within a team of experienced professionals and alongside a dedicated mentor, your future career guide. Personalized support will help you develop autonomy and successfully achieve your academic goals!

Are you currently enrolled in an engineering school or pursuing a Master’s degree in Data Science or Energy, and looking for a 6-month final-year internship starting in January 2026?

Do you have strong skills in Data Science and Machine Learning?

Do you master the development of neural network models?

Are you interested in the wind energy sector and eager to contribute to its growth?

Do you code confidently in Python and write clean, efficient code?

Can you communicate effectively in both French and English?
(All deliverables and written work during the internship will be in English.)

If this sounds like you, don’t wait—apply now and join our team!