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Senior Scientist, Quantum Sensing (Modeling and Control)

🕒 6 days ago
Quantum SensingQuantum ControlOptically Pumped MagnetometersHigh-precision Magnetometry
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📜 Description

  • Develop quantum control algorithms and software-layer controls for optically pumped magnetometers.
  • Apply statistical filtering, including Kalman and particle filters, to improve sensitivity and reduce noise.
  • Analyze time series and develop platform and environmental noise-compensation methods using digital signal processing and machine learning.
  • Simulate atomic systems to explain and guide experiments.
  • Develop, document, and review software in Python, and collaborate across sensing teams.
  • Present and document findings for colleagues, external stakeholders, and customers, including through publications and technical reports.

🛠️ Requirements

  • Expertise with Python programming language for scientific computing.
  • Experience modelling real quantum experiments/hardware and working closely with both theoretical and experimental teams.
  • Experience with version control e.g. Git with CI/CD pipelines.
  • Demonstrated experience in improving experimental outcomes through novel signal processing or denoising algorithms.
Full job description
About the team
Q-CTRL’s Quantum Sensing Research team performs basic and applied research in quantum sensing and quantum-enabled navigation. It is a highly dynamic team comprising approximately 30 specialists in theoretical and experimental atomic physics, cold-atom interferometry, navigation modeling, and modern Bayesian estimation and signal processing techniques.
The Quantum Sensing Research and Quantum Sensing R&D teams work closely together, translating novel quantum sensing research into a useful capability and product. We are focussed on pushing the boundary of what is possible in quantum sensing and ensuring our R&D has real-world impact.

About the role
This opportunity will focus on developing next-generation, small-form-factor quantum magnetometers that are both exquisitely sensitive and able to operate reliably in harsh fielded environments.

To do this, you will design novel quantum control schemes and software-layer controls for optically pumped atomic magnetometers. You will also implement advanced statistical filtering techniques allowing performance improvements in noisy operating environments.

The algorithms, signal processing, and data analytics developed by you and the rest of the team will inform the design, build, and operation of our quantum sensors. In all cases, a major focus is on real-world performance in real-world environments.

About the team Q-CTRL’s Quantum Sensing Research team performs basic and applied research in quantum sensing and quantum-enabled navigation. It is a highly dynamic team comprising approximately 30 specialists in theoretical and experimental atomic physics, cold-atom interferometry, navigation modeling, and modern Bayesian estimation and signal processing techniques.    The Quantum Sensing Research and Quantum Sensing R&D teams work closely together, translating novel quantum sensing research into a useful capability and product. We are focussed on pushing the boundary of what is possible in quantum sensing and ensuring our R&D has real-world impact. About Q-CTRL Q-CTRL is the global leader in AI-powered quantum control infrastructure software. We build the tools that make quantum technology useful, solving the hardest challenges in quantum computing and quantum sensing to deliver real-world impact.   Founded in 2017, we operate globally with offices in Sydney, Los Angeles, San Francisco, Huntsville, Berlin, and Oxford. Our teams bring together technical and multi-disciplinary expertise across the product lifecycle, and we’re hiring talent to help scale every part of the business. We work quickly to turn cutting-edge science into deployable technology.   In 2024 we raised US$113 million in Series B funding, the largest aggregate investment for a quantum software company. Six months later we delivered the first commercial quantum advantage with Ironstone Opal, our field-validated quantum navigation solution for defense and industry.   At Q-CTRL, we prioritize outcomes over hours. We offer flexibility, equity potential, and competitive benefits that reflect our high-performance culture. If you’re ready to help shape the future of quantum, we’d love to hear from you!   Please be advised that our communications will only come from the @q-ctrl.com domain. All our active job postings are available on our company website.   To recruitment agencies, we do not accept unsolicited branded profiles and are not responsible for any fees related to unsolicited resumes.

What you'll be doing:

  • Develop quantum control algorithms to improve the sensitivity and robustness of optically pumped magnetometers.
  • Use statistical techniques such as Kalman and particle filters to improve sensitivity and remove noise.
  • Perform time series analysis and develop platform and environmental noise compensation techniques using state-of-the-art digital signal processing and machine learning methods.
  • Write simulations of atomic systems to explain and guide experiments.
  • Develop, document, and review high-quality software using Python.
  • Collaborate with your colleagues in the Quantum Sensing Team, the Quantum Sensing Division, and the company more broadly.
  • Share your insights into control-augmented quantum sensing with the broader Quantum Sensing Division, company, external stakeholders and customers through verbal presentations and written outlets (e.g. academic publications, technical reports, blog posts).
  • Other duties within the Employee's skills and experience, or with reasonable training.
  • Ideally you'll have:

  • A PhD (or equivalent industry experience) in Physics, Engineering or a closely related discipline
  • Experience with high-precision magnetometery.
  • Experience in the theory, numerical modelling, and/or optimisation of one or more of the following: atomic spin ensembles, quantum sensing in warm atomic vapours, pulse-level optimisation and quantum control techniques.
  • Knowledge of statistical techniques such as Kalman and particle filtering, estimator theory.
  • Experience in time and frequency digital signal processing, e.g. adaptive filtering, Kalman filtering, match filtering.
  • Contributing to a software system architecture with multiple components developed by different teams, adhering to best-practice software development principles.
  • Bonus points if you have (but not a necessity):

  • Expertise with Python programming language for scientific computing.
  • Experience modelling real quantum experiments/hardware and working closely with both theoretical and experimental teams.
  • Experience with version control e.g. Git with CI/CD pipelines.
  • Demonstrated experience in improving experimental outcomes through novel signal processing or denoising algorithms.
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