Senior Quantum Applied Research Scientist, Physics Modeling

Posted 4 Days Ago
Be an Early Applicant
3 Locations
In-Office or Remote
192K-305K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead research and development of high‑fidelity, physics‑based quantum device models, noise models, and synthetic data pipelines. Build GPU‑accelerated simulation frameworks, validate models against experiments, and collaborate with product, engineering, and research teams to enable fault‑tolerant quantum hardware simulation and real‑time modeling.
Summary Generated by Built In

At NVIDIA, we're solving the world's most exciting problems with our unique approach to accelerated computing. We're looking for a passionate scientist at the intersection of quantum device physics and advanced physics simulation and modeling. This role will path-find the future of high-fidelity, real-time models for fault-tolerant quantum hardware.

At NVIDIA, we want to help accelerate the entire quantum ecosystem. As a Sr. Quantum Applied Research Scientist, you will help design and build high-fidelity models grounded in device physics, calibration experiments, decoding, and system performance. You will develop physics-informed data generation pipelines, advanced physics models, and advanced noise models. Your research will translate qubit physics into performant, accelerated modeling systems for fault-tolerant quantum computing for both offline and real-time use. You will collaborate with teams across Product, Engineering, and Applied Research to push the frontier of Accelerated Quantum Supercomputers! Do you love developing new technology, enjoy working with people and teams around the world, and operating at the speed of light? If yes, we would love to hear from you!

What you'll be doing:

  • Research and develop advanced physics-based models and scalable simulation frameworks.

  • Build physics-informed synthetic data generation pipelines that leverage quantum device models, noise channels, and Hamiltonian characterization to produce high-quality datasets.

  • 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.

  • Develop GPU-accelerated implementations to ensure the full simulation and modeling pipeline scales.

  • Communicate research findings and collaborate with academic and industry partners to advance the field, while championing rapid innovation, technical depth, and creative problem solving.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 12, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • Master's degree in Physics, Computer Science, Electrical Engineering, Applied Mathematics, or related field (or equivalent experience)
  • Ph.D. in a related field
  • 8+ years experience in quantum systems, physics-based modeling, simulation, or related research areas
  • Hands-on expertise developing high-fidelity physical system models, numerical simulation, and model validation
  • Strong background in quantum device physics and quantum information science, including noise models, error mechanisms, and fault-tolerant systems
  • Broad understanding of quantum control, including pulse-level hardware interfaces and classical feedback
  • Experience with scalable computing or accelerated systems for simulation and modeling workflows
  • Excellent communication and collaboration skills
  • Experience developing simulation frameworks or digital twins of quantum systems and deploying them in calibration/control workflows
  • Deep expertise in modeling, extracting, and validating noise processes, including system identification and parameter estimation
  • Experience with physics-informed or generative approaches to synthetic data generation (e.g., Hamiltonian learning, noise simulation)
  • Experience modeling multiple qubit modalities, including neutral atom qubits
  • Proficiency with CUDA and NVIDIA GPU programming for accelerating simulation or scientific workloads

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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