# PhD Research Intern, Generative AI

**Company**: NVIDIA
**Location**: Santa Clara
**Experience**: entry
**Job type**: internship
**Salary**: $30 - $94 per hour
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/PhD-Research-Intern--Generative-AI---2026_JR2016035?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_1ef79a1c-679

## Description

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.

### Responsibilities

- 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.

### Requirements

- 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

- 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.

## Skills

### Required
- Python
- PyTorch
- Generative AI
- Computer Vision
- Multimodal Learning
- Robotics
- Reinforcement Learning

### Nice to have
- Large-scale Foundation Model Training
- Video Models
- VLMs
- World Models
- Autonomous Driving
- Distributed Training
- Simulation
- Embodied AI

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/PhD-Research-Intern--Generative-AI---2026_JR2016035?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)