Quantum Research Scientist Intern

Quantum Computing

QuantumResearchScientistIntern-Fall2026

$0–0k United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Entry candidates.

The Brief

“Quantum Research Scientist Intern - Fall 2026 at Quantum Research Scientist Intern. Skills: Quantum error correcting code discovery, AI and automation for quantum code design, Python, quantum computing fundamentals. Develop automated high-performance quantum error correcting code discovery pipelines.. Develop automated quantum error correcting code discovery protocols and pipelines.”

What You'll Achieve.

discover and ultimately design high-performance quantum error correcting codes for realistic quantum systems.

Industry & Context.

Quantum Computing
Problems you'll solve

problem-solving

What They're Looking For.

Must Have

Pursuing a Master's, or PhD in Physics, Electrical/Computer Engineering, Computer Science, or a related field., Proficiency in Python, Background in quantum computing fundamentals, Familiarity with, or ability to quickly ramp up on, standard quantum superconducting qubit chip design software., Exposure to electromagnetic simulation tools such as Ansys HFSS, Palace, or comparable solvers.

Nice to Have

Hands-on experience with tensor network, state vector, or quantum error correction methods for quantum circuit simulation., Experience building agentic or LLM-driven workflows for scientific automation and tool orchestration., GPU-accelerated simulation experience with cuQuantum, CUDA-Q, or related NVIDIA quantum software., Familiarity with classical machine learning methods., Publications in quantum computing or applied physics venues (e. g. , PRX Quantum, Quantum, npj Quantum Information).

What You'll Do.

Develop automated high-performance quantum error correcting code discovery pipelines.

Develop automated quantum error correcting code discovery protocols and pipelines.

Use AI and automation to identify novel quantum error correcting codes that achieve high-performance across encoding rate

and system realizability.

Integrate various classical machine learning methods for identifying high-performance code constructions

as well as building bespoke machine learning models tailored to high-performance code design.

Build out methods to identify high-performance error correcting codes that directly incorporate hardware constraints of various types of physical systems.

Analyze and evaluate the performance of fault-tolerant circuits implementing quantum error correcting logic and memory using analysis and simulation tools.

How You'll Work.

Communication Scope

communication

Full 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 Research Scientist Intern to develop automated high-performance quantum error correcting code discovery pipelines. 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 develop techniques at the intersection of quantum code design and AI-driven automation, prototyping large scale protocols to computationally discover and ultimately design high-performance quantum error correcting codes 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, as well as building bespoke machine learning models tailored to high-performance code design. * Building out methods to identify high-performance error correcting codes 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:** ** * Pur

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