Applied Physics ML Research Intern - Fall 2025

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We're looking to grow our company, and form teams with the most inquisitive people in the world. Join us at the forefront of technological advancement. NVIDIA's deep learning and HPC platforms have made major impact to various fields is broadly used across leading academic institutions, research labs, start-ups, and industry, including world's largest companies. We are looking for a passionate, hard-working and creative intern to help us take on more of these unique opportunities in HPC and deep learning solutions What you'll be doing: Work with some of the brightest minds in a leading AI company to research, develop and implement methods for AI driven real world science and engineering problems Stay up to date with the latest research and innovations in deep learning techniques, publish papers, attend conferences and interact/work with universities, national labs and industry to demonstrate thought leadership in AI driven computational sciences and engineering What we need to see: Pursuing a Masters or PhD in computer science, computational science/engineering, or related technical field Python programming skills Knowledge of neural networks as well as traditional machine learning techniques and algorithms Solid background with neural network architectures (CNN variants, LSTMs, GANs, GNNs, Diffusion models, etc.) and experience in developing or using major deep learning frameworks (e.g. TensorFlow, PyTorch, etc). Experience with solving and using machine learning for real world problems involving scientific/engineering simulations (e.g. CFD, life sciences, high energy physics, climate, oil & gas, structural, quantum chemistry, electromagnetics, optics, acoustics etc.) and/or scientific visualization is a big plus Ways to stand out from the crowd: Knowledge of optimization, geometry, parallel computing Application of machine learning techniques to physics and possibly sensor/imaging data Published papers in AI driven computational sciences and engineering in a conference or journal in the last 5 years Hands-on experience in developing generative AI models

NVIDIA is the world leader in accelerated computing, having pioneered this field to address challenges that others could not. Through its groundbreaking work in artificial intelligence and digital twins, NVIDIA is driving transformation across some of the world's largest industries, making a significant and lasting impact on society.