Research Scientist - World Modeling

On-siteSeniorResearch Scientistposted 16mo ago

✦Role summaryAI-generated

You will lead research on the PAN world model project, developing large‑scale video generation and action‑conditioned world models that simulate and predict physical interactions. Your work will translate breakthroughs into deployable systems for robotics and embodied AI, while publishing findings at top venues.

Skills required

Video generation World modeling Action-conditioned modeling Robotics Embodied ai Foundation models Simulation Prediction AI Machine learning Computer vision Generative AI Data pipelines Deep learning PyTorch

About this role

About the Institute of Foundation Models

The Institute of Foundation Models (IFM) at MBZUAI is a research lab dedicated to meaningful foundation model research — building models from scratch, understanding them deeply, and publishing work that shapes the field. You’ll work alongside world-class researchers and engineers on problems that directly define the models we ship.

The Role

Join the PAN world model project — our effort to build world models: foundation models that simulate, predict, and interact with the physical world. As a Research Scientist, you’ll drive the core research behind PAN — large-scale video generation, interactive and action-conditioned world models, and their applications in robotics and embodied AI — and publish at top venues while turning breakthroughs into working systems.

What You'll Do

Conduct original research on video world models, video diffusion models, and action-conditioned generation — from idea to publication and deployment.

Design pre-training and post-training recipes for large-scale diffusion transformers, including scaling-law studies for video pre-training.

Advance world action models / video action models and their applications in robotics and embodied agents.

Develop rigorous evaluation 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 (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, RSS, CoRL).

Research experience with state-of-the-art video generative models and world models (e.g., Cosmos-3, LTX 2.3, Self-Forcing, Lingbot-World, or comparable systems).

Deep expertise in at least one of the following areas:

Full-stack data pipelines — large-scale video data pipelines and/or simulation data collection; annotation and filtering workflows for video / world model training.
Model training & infrastructure — training large-scale diffusion transformers on large GPU clusters.
Rendering engines & simulation — Unreal Engine and Blueprint-based gym environments, game-engine integration, building interactive simulated environments.
World action models & robotics — world action models / video action models, action-conditioned video generation, world-model applications in robotics.

Strong systems and engineering expertise in deep learning frameworks such as PyTorch.

Highly proficient with modern AI coding agents and web-based coding tools (e.g., Claude Code, Codex, Cursor), and skilled at leveraging them to dramatically accelerate research workflows.

Exceptional problem-solving skills and the ability to navigate ambiguity in rapidly evolving research areas.