Research Scientist Intern, Policy Learning for Robotics (PhD)

What you'll do

• Develop and implement efficient, robust strategies for training dexterous robot manipulation policies.
• Implement and optimize methods on large-scale cluster infrastructure.
• Collaborate on demos and experiences, and prepare research for conferences, journals, or workshops.

What they ask for

• Currently pursuing a PhD in computer science, machine learning, computational mathematics, or a relevant technical field.
• Proficient in Python; experience implementing numerical methods and/or deep learning models in large-scale code.
• Must obtain and maintain work authorization in the country of employment.
• Intent to return to the degree program after the internship and availability for a minimum 16 consecutive week internship.

Nice to have

• Experience training deep learning models, familiarity with PyTorch, and experience with distributed large-scale training on CPU/GPU clusters.
• Research track record, such as grants, fellowships, patents, or first-authored publications at leading workshops or conferences.

Pay

$7,650/month to $12,667/month (base salary)

Tools

Python, PyTorch, CPU/GPU clusters

AI focus

Research and develop reinforcement learning and robotic policy-learning algorithms for dexterous manipulation, including diffusion and flow models, vision-language-action models (VLAs), and sim2real.