Research Intern, World Models and Synthetic Data for Autonomous Driving - Summer 2027

Responsibilities

• Research and prototype generative world models, traffic world models, and synthetic-data generation methods for autonomous driving.
• Develop traffic world models that capture multi-agent interactions and realistic, reactive behaviors, enabling simulation and generation of complex driving scenarios.
• Develop methods for controllable generation of diverse, interactive, and safety-critical driving scenarios.
• Explore how generative video models, multimodal foundation models, traffic simulation, data curation, active learning, self-supervised learning, and simulation can improve training-data quality, diversity, and coverage.
• Design and conduct experiments to understand how generated data affects AV model performance, robustness, and generalization.
• Translate recent advances in generative modeling and machine learning into practical approaches for autonomous driving.
• Collaborate closely with researchers and engineers across NVIDIA on research prototypes and experimental systems.
• Contribute to high-impact research publications and open research efforts.
• What we need to see
• Currently pursuing a Ph.D. or M.S. in Computer Science, Electrical/Computer Engineering, Robotics, or a related field, with research experience in deep learning, computer vision, generative modeling, multimodal learning, robotics, or autonomous driving.

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