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

What you'll do

• Research and prototype world models and synthetic-data methods for autonomous driving, including controllable generation of complex, safety-critical scenarios.
• Design experiments to assess how generated data affects AV model training, performance, robustness, and generalization.
• Collaborate on research prototypes and contribute to research publications and open research efforts.

What they ask for

• Currently pursuing a Ph.D. or M.S. in Computer Science, Electrical/Computer Engineering, Robotics, or a related field, with research experience in a relevant area.
• Strong machine-learning and deep-learning foundations, with hands-on experience developing and evaluating neural-network models.
• Experience in at least one of: generative models, video generation, multimodal learning, 3D computer vision, autonomous driving, or robotics.
• Strong Python programming skills and experience with modern deep learning frameworks.

Nice to have

• Publications or research projects at NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or related venues.
• Experience with generative world models, video generation, diffusion or autoregressive models, multimodal foundation models, synthetic-data generation, or large-scale video, driving, robotics, or simulation datasets.

Pay

20 USD - 71 USD per hour (intern hourly rate)

Tools

Python, NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV

AI focus

Research and develop generative world models, multimodal and video-generation methods, and synthetic-data systems for autonomous driving; study how generated data can improve AV models.