Function: Intern H/F
Contract: Internship agreement
Starting date: As of March 2026 (to be defined)
Duration: 6 months
Workplace: IPVF – 18 bd Thomas Gobert, 91120 Palaiseau (France)
Education: M2, Engineering school in data, modeling, physical science
Ref.: PR-C-M-2-ST
IPVF – Institut Photovoltaïque d’Île-de-France
IPVF is a scientific and technical pole dedicated to the research and development of solar technologies. It permanently hosts its own staff, as well as the employees of its partners and external companies. IPVF aims to become one of the world’s leading centers for research, innovation, and training in the field of energy transition.
IPVF primary objective is to improve the performance and competitiveness of photovoltaic cells and develop breakthrough technologies by relying on four levers:
• Ambitious research program.
• The hosting of more than 200 researchers and their laboratories on its Paris-Saclay site.
• A state-of-the-art technology platform (8,000 m²) open to the photovoltaic industry actors, with more than 100 state-of-the-art equipment units located in clean rooms.
• A training program mainly based on a master’s degree, the supervision of PhD students, and continuing education.
INTERNSHIP CONTEXT
Perovskite solar cells are intensively investigated at IPVF and researchers collaborate to develop better performing and more reliable devices which is crucial for the next generation of solar cells. This includes establishing fabrication processes and characterizing materials and devices along fabrication steps, all supported by theoretical studies. Furthermore, a dedicated team focusses on measuring and assessing the performances of the perovskite solar cells along time, under various stresses and outdoor conditions. Finally, simulation tools have been coded to analyze such measurements, distinguish degradation causes and support the fabrication teams in developing reliable solar cells.
MAIN MISSIONS
The objective of this work is to build on the team’s ongoing efforts in coupling AI, characterizations and modeling to study the aging and self-healing of perovskite solar cells. This will involve :
👉 Enhancing indoor cycling and recovery measurements and recovery analysis, complemented by additional characterization when needed.
👉 Implementing Machine learning methods to analyze these phenomena.
👉 Depending on the progress and experimental results available, outdoor dark tests could be carried out to assess and better understand recovery mechanisms.
PROFILE
📖 Skills
- Data science
- Physical/material science
- Matlab/Python computing
- Knowledge in photovoltaics is a plus
- Fluency in English
💡Know-how
- Result oriented
- Innovative
- Team work
CONTACT
CV to be sent with reference PR-C-M-2-ST to:
Antoine.burgaud@ipvf.fr ; guillem.alvarez@ipvf.fr ; jean-baptiste.puel@edf.fr