Senior Scientist - Quantum Compilation

Q-CTRL•Los Angeles, CA

About The Position

The Quantum Computing Research team is dedicated to developing innovative methods to get the best possible performance from contemporary and next generation quantum computers. We push toward quantum advantage by developing cutting-edge applications, employing AI, control theory, and physics principles to optimize and automate critical parts of the quantum computing stack. We conduct pioneering research looking toward the near future, including quantum error correction and the integration of quantum computers with high performance computing and data centers. We are seeking a Research Scientist / Senior Research Scientist to focus on quantum compilation. You will work within a team of researchers dedicated to pushing the limits of quantum compilation. In particular, you will develop efficient and reliable methods and tools that solve challenges facing real quantum computers. Stay informed about the latest advances in quantum computing and quantum control, and leverage this knowledge to implement and refine cutting-edge methodologies. Utilize methods from a range of fields, including control theory, optimization, machine learning, computer science, and data analysis. Create code for optimizing quantum algorithms, applications, and quantum error correction schemes. Collaborate with engineering teams to translate your ideas into production-quality software. Explain and present your work in clear and accessible language. Write articles for publication in peer-reviewed journals, attend and present your work at conferences, and collaborate with other industrial and academic research groups. Use open-source scientific computing packages like Qiskit, NumPy, Networkx, Scipy, Scikit-learn, and PyTorch to build high-quality research code to develop, demonstrate, and test new algorithms and methods.

Requirements

An advanced degree in Physics, Engineering, Mathematics, Computer Science, or a related discipline. A PhD is preferred, but we will also consider exceptional individuals with previous industry experience.
Expertise in quantum computing, quantum algorithms, or quantum control. Specifically, for this role we would like to see expertise in quantum circuit compilation, qubit routing, or layout selection.
A track record of conducting impactful research, demonstrated through publications and/or presentations in well-regarded journals and/or conferences.
Experience in developing software for scientific experiments using one of the commonly-used languages such as Python, Julia, Matlab, or Mathematica (our team primarily uses Python).

Nice To Haves

Experience with high-performance languages such as Rust, C++, or Julia.
Experience with GPUs, TPUs, and other forms of hardware-accelerated computing.
A strong background in relevant methods from fields such as control theory, optimization, machine learning, or data analysis.
Familiarity with error suppression techniques used in quantum computing, such as dynamical decoupling, readout mitigation, zero-noise extrapolation, Pauli twirling, or pulse-level optimization.
Familiarity with executing circuits in Qiskit.
Familiarity with quantum error correction (QEC)
Exceptional scientific communication skills, evidenced by a track-record of teaching, scientific outreach, writing, producing elegant figures and visualizations, and/or speaking in front of both general and expert audiences.

Responsibilities

Develop efficient and reliable methods and tools that solve challenges facing real quantum computers.
Stay informed about the latest advances in quantum computing and quantum control, and leverage this knowledge to implement and refine cutting-edge methodologies.
Utilize methods from a range of fields, including control theory, optimization, machine learning, computer science, and data analysis.
Create code for optimizing quantum algorithms, applications, and quantum error correction schemes.
Collaborate with engineering teams to translate your ideas into production-quality software.
Explain and present your work in clear and accessible language.
Write articles for publication in peer-reviewed journals, attend and present your work at conferences, and collaborate with other industrial and academic research groups.
Use open-source scientific computing packages like Qiskit, NumPy, Networkx, Scipy, Scikit-learn, and PyTorch to build high-quality research code to develop, demonstrate, and test new algorithms and methods.