In this role, you will use machine learning to develop automated discovery pipelines for Quantum Error Correction (QEC). You will be responsible for using machine learning to uncover new and novel codes for fault-tolerant quantum computing, specifically tailoring these discoveries for superconducting qubits and high-connectivity platforms. You will develop large scale pipelines to programmatically discover and analyze QEC schemes. These pipelines will help to improve error correcting codes used for modular architectures addressing challenges such as entangling links between chips that are slower or more faulty than on-chip gates, improve fault tolerant gate implementations and close the gaps between theoretical code frameworks and practical hardware implementation considerations. In this capacity, you will operate at the intersection of machine learning and quantum physics to guarantee that the discovered codes are rigorously optimized for both current and next-generation quantum processors. Beyond the technical design, you will contribute to the wider research community by sharing and publishing your findings. These contributions will be inspired by internal projects as well as through active collaborations with research programs at partner universities and technical institutes globally.
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.
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
- Explore automated Quantum Error Correction discovery with machine learning to uncover new and novel quantum codes that achieve high encoding rate, high distance, or favorable layout in hardware.
- Apply Machine Learning algorithms to adapt error correction circuits to hardware constraints on connectivity, and analyze fault-tolerant circuits for syndrome measurement and logical operations.
- Analyze fault-tolerant circuits for syndrome measurement and logical operations.
- Simulate quantum codes under noise models and evaluate performance.
Qualifications
Minimum qualifications:
- PhD degree in Quantum Computing, Math, Physics, Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
- One or more scientific publication submissions for conferences, journals, or public repositories in the fields of machine learning or quantum computing.
Preferred qualifications:
- 1 year of experience owning and initiating research agendas.
- 1 year of experience in Quantum computing.