Research Scientist, Numerical Modeling, Quantum AI

Applicants in San Francisco:
Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Note:

By applying to this position you will have an opportunity to share your preferred working location from the following: Goleta, CA, USA;
San Francisco, CA, USA.Minimum qualifications:

• PhD degree in quantum information related field, Physics, Electrical Engineering, or related field.
• Experience in theoretical quantum physics.
• One or more scientific publication submission(s) for conferences, journals, or public repositories (such as Physical Review, AAAS, Nature and npj, etc.).

Preferred qualifications:

• 2 years of coding experience.
• Experience in numerical physics and scientific/high-performance computing.
• Familiarity with quantum error correction.

About the jobAs 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.

As a part of the Modeling team, you will develop theoretical and numerical models to support the design, calibration, and operation of our superconducting qubit-based processors. You will provide an understanding of the physical phenomena that occur in our devices as work lies at the intersection of physical insight, metrology, and engineering, and is necessary for the success of Google Quantum AI's mission to build a useful, error-corrected quantum computer.

In this role, you will develop experimental protocols to measure coherent errors at large scales as it will leverage advanced simulation and fitting techniques to implement noise learning.

The full potential of quantum computing will be unlocked with a large-scale computer capable of error-corrected computations. Google Quantum AI's mission is to build this computer and unlock solutions to classically intractable problems. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

• Develop, apply, and scale noise learning and other Quantum Characterization, Verification, and Validation (QCVV) methods to build predictive models of coherent and incoherent errors in superconducting qubits.
• Leverage heavy compute resources to run simulations and numerical optimization in support of noise learning.
• Guide or directly contribute to software packages supporting these efforts.
• Collaborate with experimentalists to support device characterization and error mitigation efforts, for example by proposing calibration experiments and analyzing experimental data.
• Extend noise learning techniques to work in Quantum Error Correction (QEC) experimental contexts and integrate inferred error metrics into comprehensive error budgets of logical error.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law.

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