Research Scientist - World Modeling
Role Overview
Join the PAN world model project, building foundation models that simulate, predict, and interact with the physical world.
Research spans large-scale video generation, interactive and action-conditioned world models, robotics, and embodied AI.
The role drives core research, publication, and translation of breakthroughs into working systems.
Key Skills for This Role
Full Job Posting
About the Institute of Foundation Models
IFM at MBZUAI is a research lab focused on foundation model research, building models from scratch, understanding them, and publishing work that shapes the field.
Researchers and engineers work on problems that help define the models the institute ships.
The role
Join the PAN world model project, building foundation models that simulate, predict, and interact with the physical world.
Research spans large-scale video generation, interactive and action-conditioned world models, robotics, and embodied AI.
The role drives core research, publication, and translation of breakthroughs into working systems.
What you'll do
- Conduct original research on video world models, video diffusion models, and action-conditioned generation through publication and deployment.
- Design pre-training and post-training recipes for large-scale diffusion transformers, including video pre-training scaling-law studies.
- Advance world action models and video action models for robotics and embodied agents.
- Develop benchmarks for physical accuracy, controllability, and interactivity.
- Collaborate with engineering and data teams on large-scale training, data curation, and simulation-based data generation.
What we're looking for
- PhD in Machine Learning, Computer Science, Computer Vision, Robotics, or a related field, with first-author publications at top-tier venues.
- Research experience with state-of-the-art video generative models and world models, including comparable systems to the examples listed.
- Deep expertise in at least one area: video data pipelines and simulation data; large-scale model training and infrastructure; rendering and simulation; or world action models and robotics.
- Strong systems and engineering expertise in deep learning frameworks such as PyTorch.
- High proficiency with modern AI coding agents and web-based coding tools, such as Claude Code, Codex, or Cursor, to accelerate research workflows.
- Exceptional problem-solving and ability to navigate ambiguity in rapidly evolving research areas.
Nice to have
- Experience accelerating diffusion inference, including distillation, few-step generation, or real-time interactive generation.
- Experience with visual tokenization and multimodal foundation models.
- Experience deploying world models in robotics or embodied-AI settings.
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