Job Type
Job Details
- PhD degree in Physics, a related field, or equivalent practical experience.
- Experience developing Python software to mine and analyze datasets.
- Experience developing, validating, and deploying predictive models.
- One or more scientific publication submission(s) for conferences, journals, or public repositories.
Preferred qualifications:
- 2 years of experience in coding.
- 1 year of experience owning and initiating research agendas.
- Experience calibrating, operating, and benchmarking quantum systems.
- Experience engineering software to implement statistical analysis, optimization, and/or machine learning routines.
The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, 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.
As a member of the System Optimization and Stability team, you will develop qubit error models, benchmarks, and calibration/optimization protocols that enable and stabilize high performance on state-of-the-art superconducting quantum processors. You will also develop tools to mine and analyze large datasets to extract physical insights that inform the future of our quantum control and hardware architectures.
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.
- Develop and deploy metrology tools to characterize component and system performance of quantum processors at scale.
- Deploy, monitor, and improve automated calibrations to achieve and stabilize high fidelity quantum gates, readout, and algorithm performance.
- Assist with the design and development of software for state of the art quantum control systems.
- Work in a collaborative environment to deploy new control systems and assist in the characterization of state of the art hardware.
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