PhD Research Intern, Fundamental Generative AI

Nvidia

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Work type
On-site
Location
Santa Clara, CA
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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About Nvidia

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

Nvidia currently has 1763 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1151 roles with salary data.

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TL;DR · PhD Research Intern, Fundamental Generative AI

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The PhD Research Intern, Fundamental Generative AI - 2027 will join the Fundamental Generative AI research team at NVIDIA Research. This role involves researching, designing, and implementing novel, large-scale generative AI methods while publishing original research at top machine learning venues. The intern will collaborate with various research and product teams to transfer technology to product groups. Key responsibilities include advancing generative AI methods for image, video, 3D, graph, and multimodal data, as well as exploring applications in structural biology, chemistry, drug discovery, climate modeling, and weather forecasting. Candidates should possess expertise in computer vision, 3D, NLP, or AI for science. Required skills include Python, PyTorch, and deep learning theory, with a preference for C++ and CUDA parallel programming experience.

Skills

Generative AI Python PyTorch C++ CUDA Computer Vision NLP 3D Parallel Programming Machine Learning Deep Learning Computer Architecture Multimodal Data AI for Science

What you'll do

  • Research, design, and implement novel, large-scale generative AI methods.
  • Publish original research at top-tier machine learning venues.
  • Advance generative AI methods for image, video, 3D, graph, and multimodal data.
  • Develop generative AI models for science applications like drug discovery and climate modeling.
  • Transfer developed technologies to internal product groups.
  • Utilize Python and deep learning frameworks like PyTorch for rapid prototyping.

What we're looking for

  • Currently pursuing a Ph.D. program in Computer Science, Engineering, Statistics, or a related field.
  • Strong publication record at top machine learning venues such as NeurIPS, CVPR, ICLR, ICML, ICCV, or ECCV.
  • Excellent knowledge of the theory and practice of generative AI.
  • Strong knowledge of computer vision, 3D, NLP, or AI for science.
  • Excellent programming skills in rapid prototyping environments such as Python.
  • Knowledge of common deep learning frameworks, such as PyTorch.
  • Excellent communication skills.
  • Proficiency in C++ and parallel programming, such as CUDA (preferred).

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