Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience.Experience in foundation and diffusion models, reinforcement learning, agent learning, and applied robotics.Experience in multimodal foundation models.Experience in hands-on training and publications in at least one of the following topics: LLMs; large vision-language models; video generative models and diffusion algorithms; action-based transformers.Experience in robot learning, such as reinforcement learning, imitation learning, classical control methods, etc.Experience in robot kinematics, dynamics, and sensors.Experience in control methods, including PID, model predictive control, and whole-body control.Experience in physics simulation frameworks such as MuJoCo and Isaac Sim.Experience in robot hardware design and hands-on building experience.