Quantum Research Scientist Intern - Fall 2026

Summary: NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. They are seeking a Quantum Research Scientist Intern to develop automated high-performance quantum error correcting code discovery pipelines and to help build internal IP at the intersection of quantum code design and AI-driven automation. Responsibilities: - 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 Required Qualifications: - Pursuing a Master's, or PhD in Physics, Electrical/Computer Engineering, Computer Science, or a related field - Proficiency in Python and background in quantum computing fundamentals, especially superconducting qubits and circuit QED - 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 - Good teamwork, communication, and documentation skills Preferred Qualifications: - 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) Required Skills: Python, Quantum computing fundamentals, Superconducting qubits, Circuit QED, Quantum superconducting qubit chip design software, Electromagnetic simulation tools, Ansys HFSS, Palace, Quantum error correction, Tensor network methods, State vector methods, GPU-accelerated simulation, cuQuantum, CUDA-Q, Classical machine learning methods Internship Start Date: Start in 2026 Fall Benefits: You will also be eligible for Intern benefits.