Responsibilities
Lead the development of hybrid algorithmic software in C++, MATLAB, Mathematica, and Python.
Design, adapt, and evaluate hybrid algorithms for sensor modelling, processing, data fusion, tracking, state estimation, and anomaly detection.
Apply time- and frequency-domain methods, including Fourier analysis, digital sampling, and filter design.
Review recent research and translate novel techniques into practical ASP/PNT solutions.
Improve the robustness of traditional algorithms for challenging, real-world data and systems.
Use machine learning where it adds value, particularly for non-linear dynamics and complex system behaviour.
Support proposals, bids, and project delivery for research and development activities.
Mentor junior engineers and help strengthen technical capability across the team.
Qualifications
Essential experience
- Substantial recent experience in low-TRL research and development within ASP, PNT, sensor fusion, or a related field.
- Confidence working across theory and implementation and comfortable applying hybrid white-box and black-box approaches to real engineering problems.
- Implementing hybrid algorithms that combine classical and machine‑learning approaches.
- Applied experience in one or more of: feature extraction, data fusion, target tracking, image segmentation, image matching, sensor calibration, state estimation, anomaly detection, integrity monitoring, system modelling, synthetic data generation.
- Strong understanding of time and frequency domain methods, including Fourier transforms, digital sampling, and filter design.
- Ability to evaluate, adapt, and implement techniques from recent research papers.
- Experience making algorithms robust to real-world data and complex physical system behaviour.
- Practical coding experience in C++, MATLAB, Mathematica, and/or Python.
- Proven ability to work across research, development, technical leadership, and delivery.
Desirable experience
- Knowledge of emerging sensing and PNT technologies, electronic warfare, radar, sonar, or related domains.
- Experience with EKF, UKF, Lie Group UKF, or physics-informed machine learning.
- Experience supporting bids, funding applications, or collaborative consortia.
- Exposure to contested electromagnetic environments and resilient sensing challenges.
- Experience mentoring engineers or in a technical leadership capacity.
About you
You are a technically curious problem‑solver who enjoys working at the boundary between research and practical engineering. You are able to move confidently between mathematical reasoning, software development, and applied experimentation, and you know when to use classical methods, machine learning, or a combination of both. You communicate complex ideas clearly, work well across disciplines, and are motivated by difficult problems that have real operational value. You take pride in producing high‑quality technical output and contributing to an innovative, collaborative environment.
A Bachelors degree with honours, Masters degree, or PhD in a relevant discipline is expected, along with a few years of recent experience in related research and development.
Security clearance requirement
This role requires Security Clearance (SC). It would be advantageous if currently held; otherwise, the successful applicant must undergo, achieve, and maintain SC Clearance prior to commencing employment. To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances, a minimum of 3 years’ residence in the UK over the last 5 years may be accepted, with additional overseas checks. Please visit the UKSV website for further guidance: https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels/national-security-vetting-clearance-levels.
Equal opportunity statement
At Thales, we ensure equal opportunities, pay and working conditions for all.
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