NVIDIA
QuantumErrorCorrectionResearchScientistIntern-Fall2026
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Quantum Error Correction Research Scientist Intern - Fall 2026 at NVIDIA. Skills: Quantum error correction, Code discovery, Decoder design, AI automation. Develop automated quantum error correcting code discovery protocols. Develop automated quantum error correcting pipelines”
What You'll Achieve.
Achieve high-performance across encoding rate; Achieve high-performance across error suppression; Achieve high-performance across system realizability; Improve decoding accuracy; Improve decoding scalability; Improve decoding adaptability
Industry & Context.
Error suppression; System realizability; Decoding accuracy; Scalability; Adaptability
What They're Looking For.
Must Have
Master's or PhD, Quantum computing fundamentals, Quantum error correction fundamentals, Stabilizer codes, Coding theory, Decoders, Python or similar scientific programming language, Good teamwork skills, Good communication skills, Good documentation skills
Nice to Have
Tensor network experience, State vector experience, Quantum error correction methods experience, Neural network-based QEC decoders experience, Familiarity with qubit loss, Familiarity with leakage, Familiarity with non-Pauli noise mechanisms, Magic state preparation experience, Magic state distillation experience, Magic state factory design experience, GPU-accelerated simulation experience
What You'll Do.
Develop automated quantum error correcting code discovery protocols
Develop automated quantum error correcting pipelines
Use AI for identifying quantum error correcting codes
Use automation for identifying quantum error correcting codes
Integrate classical machine learning methods
Build machine learning models
Develop machine learning-based decoders
Improve decoding accuracy
Improve decoding scalability
Improve decoding adaptability
Build methods to identify error correcting codes
Build methods to evaluate error correcting codes
Build methods to identify decoders
Build methods to evaluate decoders
Incorporate hardware constraints
Analyze fault-tolerant circuits
Evaluate fault-tolerant circuits
Implement quantum error correcting logic
Implement quantum memory
How You'll Work.
Team & Collaboration
NVIDIA team
Communication Scope
Documentation
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 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 incorpo
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