The physics team at Google AI Quantum is looking to hire a Quantum Research Scientist with expertise in NISQ quantum algorithms and system benchmarking/calibration. The candidate is expected to solve technical bottlenecks creatively with deep knowledge in physics and quantum computing as well as engineering skills.
You will work closely with the hardware team to design novel multi-qubit quantum metrology and control tools and then apply them to Google’s superconducting quantum processors
You will pursue a bottom-up approach to NISQ applications, i.e., understand our quantum hardware, learn how to calibrate many-qubit systems, mitigate coherent and incoherent errors, and run simulations/algorithms on the quantum hardware.
You will work on physics based methods for better and faster benchmarking/calibrating large-scale quantum circuits, estimation of the error budgets for NISQ algorithms, and physical based methods for error mitigation.
You will publish research results in external peer-reviewed scientific journals, present your results in international conferences, and mentor interns and postdoctoral researchers.
You will join a dynamic, passionate, and diverse team located in Venice, CA just two blocks away from the beach, enjoying the nice weather and the diverse culture in Southern California.
Basic requirements
- PhD in physics, chemistry, or electrical engineering
- Proficient with Python
- Experience in signal processing and data analysis techniques
- Knowledge of superconducting qubits
- Passionate about implementing ideas on real quantum devices
- Located in or willing to relocate to work in Los Angeles or Santa Barbara, CA
Preferred qualifications
- Experience in Cirq and quantum circuit compilation
- Proficient with Mathematica
- Familiarity with condensed matter physics and/or material aspects of superconducting qubits
Applications
- Applications should include a CV and at least three references (sent to qzj@google.com).
- Application deadline: Until the position is filled (early application is encouraged)
- Start date: ideally around June 2020