Quantum Research Scientist Intern - Fall 2026

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. NVIDIA is deeply invested in the future of quantum computing, building the accelerated platforms (cuQuantum, CUDA-Q, and NVIDIA Ising) that researchers around the world rely on to design, simulate, and scale quantum systems. This role works at the intersection of design, calibration, and quantum error correction, prototyping large-scale pipelines to computationally tackle fundamental problems in quantum hardware.

What You'll Be Doing

• Develop agentic AI systems for quantum computing applications.
• Prototype a high-performance agentic pipeline for quantum EDA (Electronic Design Automation) of superconducting qubits.
• Collect, organize, and curate data to support digital twin development and NVIDIA Ising model workflows.
• Accelerate and deploy quantum calibration primitives.
• Combine electromagnetic and quantum simulations to extract relevant parameters and construct accurate Hamiltonians of the devices.

What We Need to See

• Pursuing a Master's or PhD in Physics, Electrical/Computer Engineering, Computer Science, or related field.
• Proficiency in Python and a strong background in quantum computing fundamentals, including a deep understanding of at least one qubit modality.
• Familiarity with, or the ability to quickly ramp up on, standard design software.
• Exposure to electromagnetic simulation tools such as Ansys HFSS, Palace, or comparable solvers.
• Strong teamwork, communication, and documentation skills.

Ways to Stand Out from the Crowd

• Hands-on experience with the design, simulation, calibration, and operation of quantum hardware systems (including superconducting qubits, Ion Traps, Neutral Atoms, or other leading physical modalities).
• 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.
• A track record of publications in premier quantum computing or applied physics venues (e.g., PRX Quantum, Quantum, npj Quantum Information).