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SalaryThe 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 mission of the Quantum High Performance Simulations (HPC) subteam is to support Quantum AI with tailored HPC tools, including large Hilbert space simulations and Tensor network algorithms. We address problems such as simulation of circuit quantum electrodynamics (e.g., systems of transmons, resonators), simulation of Noisy Intermediate-Scale Quantum (NISQ) experiments (e.g., large-scale quantum circuits, continuous time evolution), and Quantum Error Correction (QEC) decoding.
Minimum qualifications:
- PhD in Quantum Physics, Quantum Computing, Computational Physics, Computational Quantum Chemistry, or equivalent practical experience.
- Experience in practical research applying Tensor network algorithms such as Matrix Product State (MPS), Multi-Scale Entanglement Renormalization Ansatz (MERA), or Projected Entangled Pair States (PEPS).
- Experience with programming in Python.
- Published research papers on applying Tensor network algorithms (e.g., MPS, MERA, or PEPS).
Preferred qualifications:
- Experience in Quantum Computing theory, Quantum Information theory and Condensed Matter theory.
- Experience with high-performance computing such as multi-CPU, GPU or multi-GPU, simulations of quantum many-body systems and/or of quantum computations, including both code development and execution of simulations.
- Experience developing novel Tensor network algorithms.
- Experience executing high-performance computing simulations such as multi-CPU, GPU or multi-GPU, based on Tensor network algorithms (e.g., MPS, DMRG, MERA, PEPS).
