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Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
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As a PhD Research Intern, Generative AI - 2026, you will join the team building Cosmos world foundation models and generative AI systems for Physical AI across robotics, autonomous driving, smart spaces, and embodied agents. You will conduct research in generative AI, multimodal foundation models, world models, and embodied AI while developing algorithms for video understanding, action-conditioned simulation, multimodal reasoning, and policy learning. Your daily work involves training and evaluating large-scale models using video, image, language, and robotics or autonomous driving data. To succeed, you must possess a strong background in computer vision, multimodal learning, or reinforcement learning alongside proficiency in Python and PyTorch. You will collaborate with researchers and engineers across AI, robotics, simulation, and graphics teams to solve complex problems involving multimodal world understanding and synthetic data generation for embodied reasoning systems.
PyTorch
Generative AI
Reinforcement Learning
Physics Simulation
3D Generative Models
Distributed Training
Data Processing Pipelines
open-source
Robotics
Python
C++
CUDA
PyTorch
JAX
TensorFlow
Deep Learning
Generative AI
Computer Vision
Large Language Models
Diffusion Models
Multimodal Foundation Models
World Models
Action-Based Transformers
Physics-Based Simulation
Synthetic Data Generation
Partial Differential Equations
Reinforcement Learning
Large Language Models
Python
PyTorch
Deep Learning
RLHF
RLAIF
Natural Language Processing
Policy Optimization
Reward Modeling
GPU Clusters
Multimodal Foundation Models
LLMs
Vision-Language Models
PyTorch
Jax
TensorFlow
Python
C++
CUDA
Reinforcement Learning
Imitation Learning
ROS
MuJoCo
Isaac Sim
Model Predictive Control
Robot Kinematics