Quantum Research Scientist Intern - Fall 2026

Nvidia

Remote Actively hiring Verified listing
Remote, US Posted 10 days ago
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At a glance

AI generated

TL;DR

As a Quantum Research Scientist Intern at NVIDIA, you will join a cutting-edge team dedicated to advancing quantum computing through the development of high-performance error correcting code discovery pipelines. Your primary responsibilities include creating automated protocols and integrating classical machine learning methods to identify novel quantum error correcting codes that optimize for performance across various metrics. You will work on building bespoke models tailored to specific hardware constraints, analyze fault-tolerant circuits using simulation tools, and contribute to the broader goal of scaling quantum systems. The ideal candidate is pursuing a Master’s or PhD in Physics, Electrical/Computer Engineering, Computer Science, or a related field with expertise in Python, quantum computing fundamentals, and experience with tensor network methods and GPU-accelerated simulations like cuQuantum and CUDA-Q. Familiarity with classical machine learning and electromagnetic simulation tools such as Ansys HFSS is also beneficial.

Skills

Python cuQuantum CUDA-Q TensorFlow PyTorch Keras Scikit-learn Ansys HFSS Palace Qiskit Cirq Tensor networks State vector simulation Quantum error correction GPU programming CI/CD

What you'll do

  • Develop automated quantum error correcting code discovery protocols and pipelines.
  • Identify novel high-performance quantum error correcting codes using AI and automation.
  • Integrate classical machine learning methods to design efficient quantum codes.
  • Build methods to identify error correcting codes that fit hardware constraints.
  • Analyze fault-tolerant circuits implementing quantum error correction logic.

What we're looking for

  • Pursuing a Master's or PhD in Physics, Electrical/Computer Engineering, Computer Science, or related field.
  • Proficiency in Python and deep knowledge of quantum computing fundamentals, especially superconducting qubits.
  • Experience with tensor network methods and GPU-accelerated simulation tools like cuQuantum/CUDA-Q.
  • Familiarity with classical machine learning for identifying high-performance code constructions.
  • Hands-on experience building AI-driven workflows for scientific automation.

Market check

Salary context

This listing doesn't show a salary. Similar roles on FindRole typically pay $117,000–$225,000.

Peer median band

$117,000–$225,000

Median floor and ceiling across peers.

Typical midpoint (25–75%)

$135,000–$201,700

Middle half of comparable postings.

Based on 240 comparable postings.

* 240 is the maximum number of comparable postings sampled.

Employer

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 801 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 797 roles with salary data.

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