---
title: PhD Research Intern, Physical AI Foundation Models
description: NVIDIA is hiring for the PhD Research Intern, Physical AI Foundation Models role
  in Santa Clara, CA. See the full description and apply.
type: job
url: https://www.foundrole.com/jobs/phd-research-intern-physical-ai-foundation-models-at-nvidia-01a0d1de-d445-748d-b951-d62cfa5f0c4e
date: 2026-09-28T03:38:01Z
og_description: Join NVIDIA as PhD Research Intern, Physical AI Foundation Models in Santa Clara,
  CA. Pays $38–$94 per hour. Full-time role.
og_image: https://www.foundrole.com/og/vox4ga.png
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  - label: Home
    url: https://www.foundrole.com/
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---

| | |
|---|---|
| **Company** | [NVIDIA](https://www.foundrole.com/companies/nvidia?utm_source=ai_markdown) |
| **Location** | Santa Clara, CA |
| **Salary** | $38/hr - $94/hr |
| **Type** | Full Time |
| **Posted** | Sep 23, 2026 |
## Description

At NVIDIA, we are building Cosmos world foundation models and generative AI systems for Physical AI across robotics, autonomous driving, smart spaces, and embodied agents.

The NVIDIA Cosmos Platform enables multimodal world understanding, simulation, synthetic data generation, and embodied reasoning. We are looking for outstanding PhD interns to help advance the frontier of Physical AI and world models.

**What you’ll be doing:**

- Conduct research in generative AI, multimodal foundation models, world models, and embodied AI.

- Develop algorithms for video understanding/generation, action-conditioned simulation, multimodal reasoning, and policy learning.

- Train and evaluate large-scale models using video, image, language, and robotics or autonomous driving data.

- Collaborate with researchers and engineers across AI, robotics, simulation, and graphics teams.

- Publish research at top conferences and transfer innovations into NVIDIA products.

**What we need to see:**

- Currently pursuing a PhD in CS, EE, Robotics, or related fields.

- Strong background in generative AI, computer vision, multimodal learning, robotics, or reinforcement learning.

- Prior publication record and research experience.

- Strong Python and PyTorch skills.

**Ways to stand out from the crowd:**

- Experience with large-scale foundation model training.

- Research in video models, VLMs, world models, robotics, or autonomous driving.

- Experience with distributed training, simulation, or embodied AI.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.


You will also be eligible for Intern [benefits](https://www.nvidia.com/en-us/benefits/interns/). ​

Applications for this job will be accepted at least until September 27, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
## Skills

- Doctor of Philosophy (PhD)
- Machine Learning Model Training
- Robotics
- Python
- Vision-Language Models (Vlm)
- Foundation Models
- Algorithms
- Distributed Training (Machine Learning)
- Computer Vision
- Generative AI
- Multimodal Machine Learning
- World Models
- Reinforcement Learning
- Embodied AI
- Generative AI Foundations
- Multimodal AI

## How to Apply

[Apply for this position](https://www.foundrole.com/jobs/phd-research-intern-physical-ai-foundation-models-at-nvidia-01a0d1de-d445-748d-b951-d62cfa5f0c4e?utm_source=ai_markdown)

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