Senior Quantum Applied Research Scientist, Physics Modeling

NVIDIA NVIDIA · Semiconductors · Redmond, WA +2 · Remote

This role focuses on research and development of advanced physics-based models and simulation frameworks for quantum computing hardware. The scientist will build physics-informed synthetic data generation pipelines, develop detailed noise models, and create GPU-accelerated implementations for scaling simulation and modeling. The goal is to translate qubit physics into performant, accelerated modeling systems for fault-tolerant quantum computing.

What you'd actually do

  1. Research and develop advanced physics-based models and scalable simulation frameworks.
  2. Build physics-informed synthetic data generation pipelines that leverage quantum device models, noise channels, and Hamiltonian characterization to produce high-quality datasets.
  3. Develop detailed noise models of quantum hardware that capture device physics, decoherence, and drift behavior, enabling accurate performance prediction and parameter inference without full experimental overhead.
  4. Develop GPU-accelerated implementations to ensure the full simulation and modeling pipeline scales.
  5. Communicate research findings and collaborate with academic and industry partners to advance the field, while championing rapid innovation, technical depth, and creative problem solving.

Skills

Required

  • Masters Degree in Physics, Computer Science, Electrical Engineering, Applied Mathematics, or a related field (Ph.D. strongly preferred); or equivalent experience.
  • 8+ years of combined experience and high impact in quantum systems, physics-based modeling, simulation, or related research areas.
  • Hands-on expertise in 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 have

  • 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 with modeling of 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.

What the JD emphasized

  • 8+ years of combined experience and high impact in quantum systems, physics-based modeling, simulation, or related research areas.
  • Hands-on expertise in 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.