NVIDIA 2027 Internships: Ph.D. Research Autonomous Vehicles

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NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create.

Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Autonomous Vehicles teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.

Learn more about Research at NVIDIA .

What you will be doing:

• Design and implement cutting-edge techniques in the field of vehicle autonomy.

• Collaborate with other team members, teams, and/or external researchers.

• Transfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.

What we need to see:

• Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship; anticipated graduation date ( month and year ) must be clearly indicated on a resume or CV to be considered.

• Depending on the internship, prior experience or knowledge requirements could include the following programming skills and technologies:

Python, C++, CUDA, Deep Learning Frameworks (PyTorch, TensorFlow, etc.)

• Strong background in research with publications at top conferences.

• Excellent communication and collaboration skills.

• Experience with large-scale model training is a plus.

Potential internships require research experience in at least one of the following areas:

• Next-Generation AV Architectures

Chain-of-Thought Reasoning

Mixture-of-Experts

Diffusion-LLMs

Diffusion-based Trajectory Decoding

• Novel Policy Training Strategies

Closed-loop Training

Off-policy RL

Online RL

Enforcing Consistency

• Foundation and Multimodal Models

Vision-language models

Multimodal reasoning

Spatial Multimodal Models

Modality Alignment

Model Scaling

Synthetic data

• Inference Efficiency

Inference Optimizations (e.g., parallel decoding, speculative decoding)

Token Representations

Model Distillation

• Simulation and Behavior Modeling

Digital Twins

Scenario Generation

World Models

Behavior/Traffic Modeling

• End-to-End AV Systems

Mapless driving

World Representations

Beyond imitation learning

Safety-aware end-to-end models

• Perception and Representation Learning

Multi-modal sensor fusion

2D/3D detection, segmentation, depth estimation, scene understanding, neural representations

• Safe and Trustworthy Autonomous Systems

Principled robustness

Model explainability

Control Barrier Functions (CBFs)

Verification and Validation of Safety-Critical AI Systems

Trustworthy AI/ML for autonomy and robotics

• Data-Strategies for AI

• Benchmarking AV

Click here to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.

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. ​

Applications are accepted on an ongoing basis.

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.