PhD Robotics Research Intern - Foundation Models

NVIDIA Corporation; Zürich; Hybrid; CHF 22,000 - 45,000; Full time

Job summary

NVIDIA Corporation seeks PhD candidate interns to contribute to robotics and AI research. You will develop algorithms, foundation models, and methods for robotic manipulation, integrating them into real-world robotic systems across multiple platforms.

You will collaborate on multi-person projects, publish results, and create AI agents to accelerate research while ensuring rigor and reproducibility. Prior publications and strong teamwork are valued.

Qualifications

• Enrolled in a PhD program in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field.
• Strong research track record with first-author work in top robotics/AI venues.
• Excellent communication and collaboration skills.
• Proficient in Python; familiarity with C++, CUDA, and Warp is a plus.
• Experience with PyTorch or JAX and robotics frameworks such as ROS2.

Responsibilities

• Develop algorithms, foundation models, and methods for robotic manipulation and loco-manipulation.
• Integrate methods into real-world robotic manipulation systems with various robot platforms.
• Contribute to multi-person research projects across robotics and machine learning stacks.
• Engage with academia through publications, conferences, and code releases.
• Develop AI agents to accelerate research while ensuring correctness and reproducibility.

Skills

Python

C++

ROS2

PyTorch

JAX

CUDA

Education

PhD student in Robotics/ML/CS/EE/ME

Tools

ROS2

Isaac Sim

MuJoCo

CUDA

Warp

Job description

NVIDIA Corporation seeks PhD candidate interns to contribute to robotics and AI research. You will develop algorithms, foundation models, and methods for robotic manipulation, integrating them into real-world robotic systems across multiple platforms.

You will collaborate on multi-person projects, publish results, and create AI agents to accelerate research while ensuring rigor and reproducibility. Prior publications and strong teamwork are valued.