Quantum High Performance Simulations Research Scientist, Quantum AI

Key Skills

Aartificial intelligence, Algorithms, GPUs, High performance computing- HPC, Python Programming

Job Description

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).

About the job

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 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.

The US base salary range for this full-time position is $136,000-$200,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Code and execute a Tensor-network based simulation algorithm for quantum many-body physics and quantum circuits.
• Help in the development and implementation of HPC simulations in specialized hardware including multi-Graphics Processing Units (GPUs).
• Collaborate in simulations of superconducting qubit systems.
• Perform quantum algorithms related research in collaboration with other team members.
• Invent and/or adapt novel simulation algorithms for quantum many-body physics and quantum circuits.