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.

You will bring substantial recent experience in low-TRL research and development, ideally within ASP, PNT, sensor fusion, or a related field. You should be confident working across theory and implementation, and comfortable applying hybrid white-box and black-box approaches to real engineering problems.
Experience implementing hybrid algorithms that combine classical and ML-based approaches.
Applied experience in one or more of the following: feature extraction, data fusion, target tracking, image segmentation, image matching, sensor calibration, state estimation, anomaly detection, integrity monitoring, system modelling, or 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.
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 acting in a technical leadership capacity.
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 few years of recent experience in related research and development.
This is an opportunity to work on technologies that support the next generation of resilient sensing and navigation capability. You will help develop solutions for challenging operational environments, contribute to future product concepts, and play a meaningful role in building technical depth across the team.
The work is ambitious, collaborative, and highly impactful - ideal for someone looking to apply advanced algorithms to genuinely complex, real-world challenges.

Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services.

Performance-related bonus
Half day every Friday, usually finishing around 13:00
28 days annual leave (plus bank holidays) with opportunity to buy up to 40 hours/year (pro rata)
24 hours volunteering paid for
Private healthcare
Pension scheme
Life cover
24/7 Employee Assistance Program and access to mental wellbeing app
Employee discount shopping schemes on major brands and retailers
Gym membership discounts

82 Scientific jobs in Benson, South Oxfordshire