Thèse CIFRE - Scenario intelligence for ADAS validation F/H
Core
Designing novel methods to classify driving scenarios in autonomous vehicle data and rigorously evaluate coverage of real and synthetic datasets using AI embeddings and generative models.
Role type
PhD researcher (Scenario Intelligence for ADAS validation)
Builds
AI-driven scenario classification and generation systems for autonomous driving validation
Domain
Automotive / Autonomous Driving / Machine Learning
Deliverable
research
Required skills
Deep learning, Generative models (World Models), Representation Learning, Python development, Latent space modeling
Preferred skills
Embedded systems validation, Autonomous driving knowledge
Technologies
Python, World Models, Embeddings
Responsibilities
Conduct literature review on representation learning for autonomous driving; Design and train optimized encoding architectures; Evaluate methods on Renault and public datasets; Develop strategies for generating missing edge cases; Publish scientific results in conferences and journals
Seniority
PhD Candidate (Researcher)