Internship - Machine Learning for optical plasma data M/F

This internship at Thales in Le Barp, located between Bordeaux and Arcachon, focuses on developing advanced analysis solutions for optical diagnostics in physics research. The intern will contribute to automating and accelerating the processing of interferometry and optical plasma spectroscopy data using machine learning techniques. The goal is to provide reliable, near real-time diagnostics for high-cadence experiments, immersing the intern in an ambitious scientific and technological project within an innovative structure.

Must Have

• Prepare a Bac+5 in Data Engineering, Applied Physics, Computer Science, Artificial Intelligence or Engineering Physics
• Seeking a final year internship of at least 6 months
• Solid foundation in mathematics and physics
• Knowledge of Python and its main scientific libraries
• Familiarity with machine learning frameworks such as TensorFlow or PyTorch
• Comfortable with image analysis, signal processing, and collaborative environments like Git
• Autonomous, rigorous, curious, and motivated by complex technical problems
• Enjoys teamwork and investing in an innovative research project with high societal impact

Perks & Benefits

• Technological expertise
• Attention to employee work-life balance
• Inclusive and benevolent environment
• Recognized societal and environmental commitment (Thales Solidarity, CAC 40 ESG index…)
• Conventioned internships
• Gratification determined by study level
• Opportunity to participate in a pioneering initiative for abundant, controllable, and decarbonized energy
• Contribution to an ambitious scientific project combining AI, experimental diagnostics, and plasma physics
• Work within a young, dynamic, and committed team
• Unique opportunity to apply advanced machine learning methods to real experimental data from international research
• Expand scientific skills
• Project towards a career in a cutting-edge technological ecosystem

Let's build a future of trust together

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Thales is a global leader in high technologies specializing in three sectors of activity: Defense & Security, Aeronautics & Space, and Cyber & Digital. It develops products and solutions that contribute to a safer, more environmentally friendly, and more inclusive world. The Group invests nearly 4 billion euros per year in Research & Development, particularly in key innovation areas such as AI, cybersecurity, quantum, cloud technologies, and 6G. Thales has nearly 81,000 employees in 68 countries.

Our commitments, your benefits

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• Our technological expertise
• Our attention to employee work-life balance
• An inclusive and benevolent environment
• Recognized societal and environmental commitment (Thales Solidarity, CAC 40 ESG index…)

Your daily life

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Our Le Barp site, located between Bordeaux and Arcachon, specializes in the development, integration, and Operational Maintenance of systems and equipment generating or amplifying very high-power signals.

As part of the development of advanced analysis solutions for optical diagnostics applied to a research field in physics, GenF is looking for an intern to contribute to the automation and acceleration of processing interferometry and optical plasma spectroscopy data. You will participate in the application of machine learning techniques and the implementation of fast and robust analysis routines, with the objective of providing reliable, near real-time diagnostics during high-cadence experiments.

This internship will offer you a concrete immersion within an ambitious scientific and technological project, at the heart of an innovative structure supported by public organizations and academic and industrial partners. You will evolve in an environment combining artificial intelligence, plasma engineering, and laser experimentation, and will contribute to the following missions:

• Conduct a state-of-the-art review on the principles of time-resolved interferometry and optical spectroscopy, as well as their traditional analysis methods.
• Implement image preprocessing routines: background subtraction, filtering, normalization.
• Develop a phase shift extraction chain using classical methods (FFT, phase unwrapping) as a reference.
• Create a learning dataset combining experimental images and synthetic data generated for training.
• Design, train, and evaluate a machine learning model dedicated to the automatic interpretation of interferograms and spectra.
• Integrate this model into a complete analysis pipeline, including data augmentation, transfer learning, and hyperparameter optimization.
• Identify sources of error, propose, and apply adapted correction routines.
• Document all developments carried out.

Your profile:

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• You are preparing a Bac+5 in Data Engineering, Applied Physics, Computer Science, Artificial Intelligence or Engineering Physics, and are looking for a final year internship of at least 6 months.
• You have a solid foundation in mathematics and physics.
• You know the Python language and its main scientific libraries, as well as machine learning frameworks such as TensorFlow or PyTorch.
• You are comfortable with image analysis, signal processing, and collaborative environments such as git.
• You are autonomous, rigorous, curious, and motivated by complex technical problems.
• You enjoy working in a team and investing yourself in an innovative research project with high societal impact.

A word from the team:

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Joining GenF means participating in a pioneering initiative aimed at developing promising technology for abundant, controllable, and decarbonized energy. You will contribute to an ambitious scientific project combining artificial intelligence, experimental diagnostics, and plasma physics, within a young, dynamic, and committed team.

This internship represents a unique opportunity to apply advanced machine learning methods to real experimental data from international research, to expand your scientific skills, and to project yourself towards a career at the heart of a cutting-edge technological ecosystem.

All our internships are conventioned and subject to a gratification whose amount is determined according to your level of study.

Thales, a Handi-Engaged company, recognizes all talents. Diversity is our best asset. Apply and join us!