Thèse CIFRE (H/F) – Sécurité des systèmes ADAS/AD basés sur des IA de bout en bout : méthodes et cadres pour la garantie de la sécurité
Core
Developing robust safety assurance methods for end-to-end AI systems in Advanced Driver Assistance Systems (ADAS) and autonomous vehicles.
Role type
PhD researcher (CIFRE) in AI safety and functional safety
Builds
Methodological frameworks for safety validation, rule-based safety monitors, and runtime confidence estimation mechanisms for autonomous driving
Domain
Automotive industry, AI safety, functional safety, autonomous systems
Deliverable
research
Required skills
Machine learning, autonomous systems, systems engineering, complex system modelling
Preferred skills
Dependability, formal verification, control theory
Technologies
Simulation environments, experimental vehicles, datasets
Responsibilities
Conduct literature review on AI safety and ADAS standards; Develop data- and simulation-based robustness frameworks; Design independent rule-based safety monitors; Develop real-time confidence estimation mechanisms; Validate solutions via simulation and physical experiments; Publish research and file patents
Seniority
PhD candidate, research-focused
