Internship, Robot Learning Research

📋 Description

• Train language-vision conditioned manipulation policies via RL in the real world
• Construct challenging and diverse suites of manipulation tasks and RL models in simulation (Isaac
• Experiment with ways of bringing policies trained in simulation to the real world
• Action-conditioned video prediction and dynamics models that stay physically consistent over long
• Use world models as learned simulators: score candidate policies offline and generate synthetic
• Build fidelity metrics that quantify where the world model can be trusted

🎯 Requirements

• Candidates pursuing or holding a master’s or PhD in computer science, machine learning, robotics
• Strong foundations in machine learning; strong Python and hands-on experience with PyTorch or JAX
• Interest in one or more of: reinforcement learning, world models and generative video
• Experience running experiments and interpreting results with rigour
• Ability to take ownership and iterate with guidance
• Strong problem-solving skills and attention to detail

🎁 Benefits

• Free daily breakfast, catered lunch, and snacks in-office
• Work at the frontier - collaborate daily with world-class engineers, researchers, and product
• Real ownership - direct access to founding leadership, meaningful input on product direction, and