Ph.D. Research Autonomous Vehicles Intern

By submitting your resume, you acknowledge that your Ph . D . Research   Autonomous Vehicles internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and you agree to our Terms of Service . We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities. 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   i nternships 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.

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