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Quantum Error Correction Research Scientist Intern - Fall 2026

Key Facts

Remote From: 
Internships
Entry-level / graduate
38 - 136K yearly
English

Other Skills

  • Communication
  • Teamwork
  • Creativity

Roles & Responsibilities

  • Pursuing a Master's or PhD in Physics, Electrical/Computer Engineering, Computer Science, or a related field (or equivalent experience).
  • Background in quantum computing fundamentals, especially quantum error correction, stabilizer codes, coding theory, and decoders.
  • Solid proficiency in Python or a similar scientific programming language.
  • Good teamwork, communication, and documentation skills.

Requirements:

  • Develop automated quantum error correcting code discovery protocols and pipelines.
  • Use AI and automation to identify novel quantum error correcting codes that maximize encoding rate, error suppression, and hardware realizability.
  • Integrate machine learning methods to identify high-performance code constructions and develop ML-based decoders for topological and/or QLDPC codes, focusing on decoding accuracy and scalability.
  • Analyze and evaluate the performance of fault-tolerant circuits implementing quantum error correction logic and memory using simulation tools.

Job description

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. 

We are looking for a Quantum Error Correction Research Scientist Intern to develop automated, high-performance quantum error correction research pipelines spanning both code discovery and decoder design. NVIDIA is deeply invested in the future of quantum computing, building the accelerated platforms (cuQuantum, CUDA-Q, and Ising) that researchers around the world rely on to design, simulate, and scale quantum systems. On this team, you will help push frontier research at the intersection of quantum code design, neural decoders, and AI-driven automation, prototyping large-scale methods to computationally discover, evaluate, and improve quantum error correction schemes for realistic quantum systems.

 

What you'll be doing:

  • Developing automated quantum error correcting code discovery protocols and pipelines.

  • Using AI and automation to identify novel quantum error correcting codes that achieve high-performance across encoding rate, error suppression, and system realizability.

  • Integrating various classical machine learning methods for identifying high-performance code constructions, building bespoke machine learning models tailored to high-performance code design, and developing machine learning-based decoders for topological and/or QLDPC codes, with an emphasis on improving decoding accuracy, scalability, and adaptability to quantum logic settings.

  • Building out methods to identify and evaluate high-performance error correcting codes and decoders that directly incorporate hardware constraints of various types of physical systems

  • Analyzing and evaluating the performance of fault-tolerant circuits implementing quantum error correcting logic and memory using analysis and simulation tools.

 

What we need to see:

  • Pursuing a Master's, or PhD in Physics, Electrical/Computer Engineering, Computer Science, or a related field (or equivalent experience).

  • Background in quantum computing fundamentals, especially the fundamentals of quantum error correction, stabilizer codes, coding theory, and decoders.

  • Solid proficiency in Python or similar scientific programming language experience.

  • Good teamwork, communication, and documentation skills.

 

Ways to stand out from the crowd:

  • Hands-on experience with tensor network, state vector, or quantum error correction methods for quantum circuit simulation.

  • Experience with neural network-based quantum error correction decoders, either for topological or QLDPC codes.

  • Familiarity with qubit loss, leakage, and other non-Pauli noise mechanisms, including methods for incorporating this information into QEC code design and decoder design.

  • Experience with magic state preparation, distillation, or factory design, including decoding and performance analysis of magic state factories.

  • GPU-accelerated simulation experience with cuQuantum, CUDA-Q, or related NVIDIA quantum software.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! 

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.


You will also be eligible for Intern benefits.

Applications for this job will be accepted at least until May 25, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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