PhD - End-to-End Trainable System for Autonomous Driving with Introspection
Core
Develop next-generation autonomous driving systems by integrating Vision-Language-Action (VLA) models, world models, and agentic planners to enable predictive, imagination-based autonomy.
Role type
PhD researcher (End-to-End Trainable System for Autonomous Driving)
Builds
A cohesive autonomous driving framework integrating VLA, world models, and agentic planners
Domain
Autonomous driving, machine learning, robotics
Deliverable
production ML models
Required skills
machine learning algorithms, deep learning, Python, C++, long-term prediction, edge-case handling, proactive simulation
Preferred skills
world models, agentic planners, unexpected scenario handling
Technologies
VLA models, world models, agentic planners, Python, C++