Senior Scientist, Quantum Compilation

• 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.

You should have:

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).

Skills we also value (one or more is desirable, but not required):

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.