Research Scientist, Applied ML, Quantum Error Correction

Job description

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.