Hybrid Algorithm Researcher

Location:

Reading, United Kingdom

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.

We are seeking a highly skilled Hybrid Algorithm Researcher to develop advanced algorithmic software for future products in Advanced Signal Processing (ASP) and Position, Navigation & Timing (PNT). This is a unique opportunity to work at the intersection of classical signal processing and AI‑based methods, applying both to complex sensing, modelling, tracking, fusion, and estimation challenges in contested electromagnetic environments. This role is ideal for someone who thrives on solving difficult technical problems and enjoys turning novel research into practical, high‑impact solutions.

You will contribute to low‑TRL research and development activities, helping to shape technologies that remain robust, adaptable, and effective in real‑world and adversarial conditions.

• 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…