Senior Research Scientist, Quantum Error Correction

Q-CTRL

Los Angeles Posted October 7, 2026

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On-site Full-time Senior
Job Description

About the team

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.

About the role

At Q-CTRL, we’re pioneering the future of quantum technology. Our Quantum Error Correction team is seeking a Senior Research Scientist to design and implement components of an end-to-end compiler and orchestrator for distributed FTQC. You’ll join a fast-paced research team, collaborating closely with engineering teams to produce high-impact research and publications and translate scientific advances into impactful software solutions.

This is your opportunity to work at the forefront of quantum computing, driving real-world innovation in a rapidly evolving field. As a Research Scientist, you’ll develop solutions for quantum technologies and deploy them across the Q-CTRL product suite.

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What you'll be doing:

  • Identify key architectural bottlenecks for a FTQC and implement efficient and reliable methods to solve key challenges facing real quantum computers.
  • Conducting innovative research on aspects of QEC, such as, but not limited to:
  • designing and optimizing decoders
  • developing compilation schemes and computation architectures for FTQC
  • optimizing logical operation schemes
  • using QEC primitives to boost near term applications
  • Stay up to date with advances in quantum computing and QEC research, applying this knowledge to develop cutting-edge methodologies.
  • Utilize methods from a range of fields, including control theory, optimization, machine learning, computer science, and data analysis.
  • Publishing high-impact papers and presenting at top conferences
  • Collaborate with engineering teams to translate your ideas into production-quality software.
  • Explain and present your work in clear and accessible language. Incorporate feedback and foster effective collaboration with colleagues.
  • 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.

Ideally you'll have:

  • A PhD degree in Physics, Engineering, Mathematics, Computer Science, or a related discipline.
  • Relevant industry or postdoctoral experience in quantum error correction. PhD graduates with proven track record in QEC research will be considered.
  • Expertise in top leading QEC codes such as the surface and qLDPC codes.
  • Expertise in one or more of the following: decoders, compilation, computation architectures.
  • 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 Python.

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

  • Experience with high-performance languages such as Rust or C++.
  • 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 or Cirq.
  • Exceptional scientific communication skills, evidenced by a track-record of teaching, scientific outreach, writing, and/or speaking in front of both general and expert audiences.
  • Familiarity with hardware, such as FPGAs or ASICs.
  • A track record of winning contracts or grants.
Required Skills
collaboration machine learning data analysis presentation skills NumPy scikit-learn PyTorch Python Rust C++ communication teaching
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