{"id":2504820,"url":"https://alion.io/job/q-ctrl-senior-scientist-quantum-sensing-modeling-and-control","title":"Senior Scientist, Quantum Sensing (Modeling and Control)","company":{"id":6563,"name":"Q-CTRL","domain":"q-ctrl.com","url":"https://alion.io/company/q-ctrl","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Science & Research","role_family":"Science & Research","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sydney, Australia"],"countries":["AU"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":77000,"max_usd":173000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1301},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"CI/CD","optional":true},{"name":"Git","optional":true}],"status":"live","first_seen_at":"2026-10-14T05:57:44Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-16T02:49:37Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About the role\nThis opportunity will focus on developing next-generation small-form-factor quantum magnetometers that are exquisitely sensitive, ultrastable, and able to operate reliably in harsh fielded environments. A key part of this role is to use the techniques of quantum control to improve the sensitivity and robustness of magnetometers. This will involve developing novel software-layer control protocols and operating modes for optically pumped atomic magnetometers, as well as advanced statistical filtering techniques, in order to deliver step-change performance improvements in noisy operating conditions.\nThe 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 - you will be taking your code and algorithms, applying them to actual, field-deployed platforms, and working to make them effective.\nAdditionally, you will contribute to the efficient and effective functioning of Q-CTRL. This will sometimes include helping out regardless of boundaries of responsibility to help us achieve our mission of making quantum technology useful.\nWhat you'll be doing:\nDevelop quantum control algorithms to improve the sensitivity and robustness of optically pumped magnetometers.\nUse statistical techniques such as Kalman and particle filters to improve sensitivity and remove noise.\nPerform time series analysis and develop platform and environmental noise compensation techniques using state-of-the-art digital signal processing and machine learning methods.\nWrite simulations of atomic systems to explain and guide experiments.\nDevelop, document, and review high-quality software using Python.\nCollaborate with your colleagues in the Quantum Sensing Team, the Quantum Sensing Division, and the company more broadly.\nShare 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).\nOther duties within the Employee's skills and experience, or with reasonable training.\nIdeally you'll have:\nA PhD (or equivalent industry experience) in Physics, Engineering or a closely related discipline\nExperience with high-precision magnetometery.\nExperience 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.\nKnowledge of statistical techniques such as Kalman and particle filtering, estimator theory.\nExperience in time and frequency digital signal processing, e.g. adaptive filtering, Kalman filtering, match filtering.\nContributing to a software system architecture with multiple components developed by different teams, adhering to best-practice software development principles.\nBonus points if you have (but not a necessity):\nExpertise with Python programming language for scientific computing.\nExperience modelling real quantum experiments/hardware and working closely with both theoretical and experimental teams.\nExperience with version control e.g. Git with CI/CD pipelines. \nDemonstrated experience in improving experimental outcomes through novel signal processing or denoising algorithms.","description_format":"text","description_chars":3407,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Australia","iso":"AU","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Quantum Science & Computing","Custom Software 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