Senior Quantum Applied Research Scientist, Physics Modeling

NVIDIA•Redmond, WA

1d•$192,000 - $304,750•Hybrid

About The Position

At NVIDIA, this scientist works at the intersection of quantum device physics and advanced physics simulation and modeling, helping develop high-fidelity, real-time models for fault-tolerant quantum hardware. The role involves designing and building models grounded in device physics, calibration experiments, decoding, and system performance. The scientist develops physics-informed data generation pipelines, advanced physics and noise models, and performant modeling systems that translate qubit physics for fault-tolerant quantum computing in offline and real-time settings. The role collaborates with Product, Engineering, Applied Research, and academic and industry partners to advance accelerated quantum computing.

Requirements

Master’s degree in Physics, Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent experience; a Ph.D. is strongly preferred.
8+ years of combined experience and high impact in quantum systems, physics-based modeling, simulation, or related research areas.
Hands-on expertise developing high-fidelity models of physical systems, including numerical simulation and model validation.
Strong background in quantum device physics and information science, including noise models, error mechanisms, and fault-tolerant quantum systems across one or more qubit modalities.
Broad understanding of quantum control, such as pulse-level hardware interfaces and classical feedback through software abstractions.
Experience with scalable computing or accelerated systems for simulation, numerical methods, or modeling workflows.
Excellent communication and collaboration skills.

Nice To Haves

Hands-on experience developing simulation frameworks or digital twins of quantum systems and deploying them in calibration or control workflows, with awareness of fidelity, latency, and scalability tradeoffs.
Deep expertise in modeling, extracting, and validating noise processes, including system identification, parameter estimation, and uncertainty quantification.
Experience with physics-informed or generative approaches to synthetic data generation, including noise simulation, Hamiltonian learning, or data augmentation for scientific workflows.
Experience modeling more than one qubit modality, including neutral atom qubits.
Proficiency with CUDA and NVIDIA GPU programming for accelerating quantum simulation, numerical modeling, or large-scale scientific workloads.

Responsibilities

Research and develop advanced physics-based models and scalable simulation frameworks.
Build physics-informed synthetic data generation pipelines using quantum device models, noise channels, and Hamiltonian characterization to produce high-quality datasets.
Develop detailed quantum hardware noise models that capture device physics, decoherence, and drift behavior for performance prediction and parameter inference without full experimental overhead.
Develop GPU-accelerated implementations so the full simulation and modeling pipeline scales.
Communicate research findings and collaborate with academic and industry partners to advance the field.