Description

NVIDIA is seeking strategic, ambitious, hard-working, and creative individuals for a Ph.D. research internship in autonomous vehicles.

The internship offers hands-on experience with one of NVIDIA's industry-leading autonomous vehicle teams.

Responsibilities:

Design and implement cutting-edge techniques in vehicle autonomy.
Collaborate with team members, teams, and external researchers.
Transfer research to product groups to enable new products or types of products, including prototypes, patents, products, and publishing original research.

Requirements:

Actively enrolled in a Ph.D. program in Computer Science, Electrical Engineering, or a related field.
Anticipated graduation date must be clearly indicated on a resume or CV.
Prior experience or knowledge in programming skills and technologies such as Python, C++, CUDA, Deep Learning Frameworks (PyTorch, TensorFlow, etc.).
Strong research background with publications at top conferences.
Excellent communication and collaboration skills.
Experience with large-scale model training is a plus.

Preferred areas of research:

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
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

Benefits: