Stage Innovation : Ingénieur Génie Logiciel / Intelligence Artificielle (domaine spatial)
Core
R&D on a satellite position prediction tool using machine learning and spatial mechanics.
Role type
Junior IC machine-learning engineer (spatial systems)
Builds
Satellite position prediction tool
Domain
Aerospace + Scientific Machine Learning
Deliverable
production ML models
Required skills
Python, scientific computing, Git, Azure DevOps, Docker, CI/CD pipelines, Linux
Preferred skills
Physics-Informed Neural Networks (PINNs), Neural Operators (FNOs, DeepONet), Scientific Machine Learning (SciML), surrogate modeling, PDEs, uncertainty quantification, digital twins, orbital mechanics, Earth observation, space thermal dynamics
Technologies
PyTorch, JAX, TensorFlow
Responsibilities
Implement machine learning models (supervised, unsupervised, optimization), implement spatial mechanics in prediction tools, manage project tasks, manage diverse databases, develop simple front/back-end demonstrators
Seniority
Intern (final year engineering student)
