Senior Research Scientist, QEC Physics Design, Quantum AI

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Google Quantum AI is building quantum computing for otherwise unsolvable problems. The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, error-corrected computations. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google (https://www.google.com/about/careers/applications/benefits/).

Minimum qualifications:

- PhD in Physics, Quantum Information, Electrical Engineering, Computer Science, or a related technical field, or equivalent practical experience.

- 2 years of post-doctoral research experience in academia or industry.

- Research experience in quantum error correction (e.g., fault-tolerant architectures, circuit-level noise simulation, or decoding) or physical noise and device modeling of quantum hardware.

- Experience developing numerical simulations and modular scientific software in Python.

Preferred qualifications:

- Experience with superconducting qubit physics, circuit QED, and physical error mechanisms (such as leakage, TLS defects, and coherent or incoherent crosstalk).

- Experience with QEC simulation and decoding tools (e.g., Stim, Clifford simulators, or custom fault-tolerance frameworks).

- Experience architecting and maintaining reusable simulation pipelines or scientific software libraries.

- Experience analyzing experimental data from multi-qubit or QEC devices to diagnose error mechanisms.

- Ability to collaborate across theory, hardware design, and experimental teams to translate physical modeling into hardware design decisions.

- Evaluate proposed processor architectures (including novel QEC codes, modular and multiplexed control schemes, and alternative superconducting qubit or gate designs) prior to fabrication to predict logical performance.

- Develop and adapt models of correlated physical error mechanisms, such as leakage and two-level system (TLS) defects, to build realistic logical error budgets beyond simplified noise models.

- Architect, build, and maintain modular end-to-end Python simulation pipelines that bridge electromagnetic and device-level physics models with processor noise models and circuit-level QEC simulations.

- Partner closely with processor design, device modeling, and QEC protocol teams to drive pre-fabrication design trade-offs and actionable hardware roadmap recommendations.

- Analyze experimental data from QEC and hardware testbed devices to validate simulation predictions and uncover unmodeled physical error mechanisms.