Student Researcher (Seed Vision – Long-Range Video Generation) – 2026 Start (PhD)

About the team

The Seed Vision Team focuses on foundational models for visual generation, developing multimodal generative models, and carrying out leading research and application development to solve fundamental computer vision challenges in GenAI.

Responsibilities

• Develop scalable architectures for long-range video generation with consistent motion, identity, and layout.
• Explore hierarchical or recurrent latent structures to support generation across long temporal spans.
• Address challenges in temporal drift, motion collapse, and high-frequency detail retention.
• Investigate autoregressive or chunked generation strategies that balance quality and memory.
• Design evaluation protocols for long video quality (e.g., realism, consistency, semantic continuity).

Qualifications

• Currently pursuing a PhD in Computer Vision, Machine Learning, or a related field.
• Research experience in generative modeling, especially for video, motion, or temporal sequences.
• First-author publications in CVPR, ICCV, ECCV, NeurIPS, ICLR, or ICML.
• Proficiency in deep learning frameworks and experience with large-scale video datasets.
• Experience with diffusion or transformer-based video models, or long-context sequence generation (preferred).
• Familiarity with long-form video datasets (preferred).
• Understanding of perceptual metrics and user-study-based video evaluation (preferred).