PhD Research Intern, Quantum Simulation and AI

Nvidia

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Quick summary

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

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Similar $181k
$113k most similar roles pay here $255k

This listing doesn't post a salary. Most similar roles pay $126,787–$235,750.

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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 892 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 870 roles with salary data.

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At a glance

TL;DR · PhD Research Intern, Quantum Simulation and AI

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The PhD Research Intern, Quantum Simulation and AI - 2027 role is situated within the research team to advance state-of-the-art quantum computing and GPU applications. You will research and develop innovative algorithms and software systems for the quantum ecosystem while collaborating with internal machine learning and programming systems teams as well as external researchers. Your daily work involves running large-scale experiments on clusters of GPUs, publishing original research at conferences, and exploring areas like tensor network methods, quantum surrogate modeling, and automated proving. The role requires a strong background in linear algebra and math for quantum computing. You will utilize Python, CUDA, and machine learning frameworks such as PyTorch, TensorFlow, or JAX to solve complex problems in quantum simulation and inverse design. This position focuses on the technical intersection of high-performance computing and quantum physics research.

Skills

Quantum Computing GPU CUDA Python PyTorch TensorFlow JAX Machine Learning Linear Algebra Parallel Computing Simulation Software Systems

What you'll do

  • Research and develop innovative algorithms and software systems for the quantum computing ecosystem.
  • Run large-scale experiments on GPU clusters to advance state-of-the-art quantum computing simulations.
  • Develop research in areas like tensor network methods, quantum surrogate modeling, and automated proving.
  • Publish original research findings and present at industry conferences and events.
  • Build software systems utilizing machine learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Implement CUDA-based solutions to optimize quantum computing applications on GPU hardware.
  • Engage with external researchers to advance the state of the art in quantum technologies.

What we're looking for

  • Currently pursuing a Ph.D. in Quantum Physics or related fields.
  • At least 1 year of relevant research experience in quantum computing with a strong research record and publications or patents.
  • Strong basis in linear algebra and expertise in math for quantum computing and tensor algebraic methods.
  • Experience with Python (preferred).
  • Experience with CUDA (preferred).
  • Experience with commonly used machine learning frameworks like PyTorch, TensorFlow, or JAX.
  • Strong communication and teamwork skills.

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