2 of 2 Permanent Signal Processing Jobs in Oxford

the role will be developing and implementing methods for removing magnetic and/or vibrational noise induced by the platform on which the quantum sensor is mounted. The algorithms, signal processing, automation, and data analytics you develop will inform the design, build, and operation of our quantum sensors for a given end-user application. What you'll be … Earth observation; Perform time series analysis and develop platform and environmental noise compensation techniques that enable high quality magnetic- and gravity-aided navigation using state-of-the-art digital signal processing and machine learning methods; Use data analytics to translate quantum sensor data streams into capabilities that solve pressing challenges for current and prospective end-users and customers … A PhD (or equivalent industry experience) in physics, geophysics, electronic engineering, computer science, mathematics, or a closely related discipline; Experience performing data analysis, algorithmic development, and/or digital signal processing in one or more of the following areas: magnetic and/or gravitational anomaly detection; airborne magnetic and/or gravitational surveying; magnetic navigation; magnetic signature and More ❯

A B.Sc .(Hon) or M.Sc . in Physics, Electronic Engineering, Mathematics or a closely related discipline. Experience in navigation theory, numerical navigation modelling (e.g. navigation system modelling, navigation signal processing, navigation fusion for alternative navigation systems, quantum sensing for navigation), and/or real-time state tracking and estimation. Finally, you will have a strong desire to … and a company that is fundamentally building the future of the quantum technology industry. It would be fantastic if you have these skills but not essential: Experience in modern signal processing methods (e.g. Bayesian methods, particle filtering, sequential Monte Carlo methods). Experience in sensor modelling and sensor signal processing, including data fusion. Familiarity with the More ❯