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Q-CTRL is seeking a Senior Scientist to join its Quantum Sensing Research team, a 30-person group focused on basic and applied research in quantum sensing and quantum-enabled navigation. The team combines expertise in theoretical and experimental atomic physics, cold-atom interferometry, navigation modeling, and advanced Bayesian estimation and signal processing.
In this role, you will develop quantum control algorithms to enhance the sensitivity and robustness of optically pumped magnetometers. You'll apply statistical techniques such as Kalman and particle filters to improve sensitivity and reduce noise. Your responsibilities include performing time series analysis, developing platform and environmental noise compensation techniques using digital signal processing and machine learning, and writing simulations of atomic systems to guide experiments.
You will develop, document, and review high-quality software using Python, collaborating closely with colleagues across the Quantum Sensing Research team, the broader Quantum Sensing Division, and the company. You'll also share insights through presentations and written outputs including academic publications, technical reports, and blog posts.
Q-CTRL, founded in 2017, is the global leader in AI-powered quantum control infrastructure software. The company raised US$113 million in Series B funding in 2024 and delivered the first commercial quantum advantage with Ironstone Opal, a field-validated quantum navigation solution for defense and industry. The company operates globally with offices in Sydney, Los Angeles, San Francisco, Huntsville, Berlin, and Oxford.
REQUIREMENTS:
- PhD (or equivalent industry experience) in Physics, Engineering, or closely related discipline
- Experience with high-precision magnetometry
- Experience in theory, numerical modeling, and/or optimization of atomic spin ensembles, quantum sensing in warm atomic vapours, pulse-level optimization, and/or quantum control techniques
- Knowledge of statistical techniques such as Kalman and particle filtering, estimator theory
- Experience in time and frequency digital signal processing (adaptive filtering, Kalman filtering, match filtering)
- Experience contributing to software system architecture with multiple components developed by different teams, adhering to best-practice software development principles
BONUS:
- Expertise with Python for scientific computing
- Experience modeling real quantum experiments/hardware and working with theoretical and experimental teams
- Experience with version control (Git) and CI/CD pipelines
- Demonstrated experience improving experimental outcomes through novel signal processing or denoising algorithms
