Hybrid Algorithm Lead Researcher

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.

Are you an expert at the intersection of deep mathematics and modern AI? Do you want to pioneer the next generation of algorithmic software for contested electromagnetic environments (CEME)?

We are seeking a Hybrid Algorithm Researcher to lead low-TRL research and development in Advanced Signal Processing (ASP) and Position, Navigation & Timing (PNT).

In this role, you won't choose between classical physics and machine learning—you will fuse them. We are looking for a pioneer to bridge the gap between white-box mathematical rigor and black-box AI adaptability to build solutions that are robust, explainable, and fast.

🧠 The Mission

• Fuse Paradigms: Apply Physics-Informed Machine Learning (PIML) and hybrid architectures to complex sensor modelling, data fusion, and target tracking.
• Defend the Spectrum: Design algorithms engineered to survive and adapt in heavily jammed, spoofed, and contested electronic environments.
• Paper to Prototype: Evaluate cutting-edge academic research, replicate novel techniques, and rapidly adapt traditional ASP/PNT algorithms for challenging, real-world data.
• Technical Leadership: Act as a Project Design Authority (PDA), contribute to high-value R&D bids, and mentor a high-innovation team of junior engineers.

🛠️ The Toolkit

• The Sweet Spot: Proven experience implementing hybrid algorithms (classical math + ML) for state estimation, anomaly detection, or information fusion.
• The Core Math: Deep familiarity with time/frequency domains, Fourier transforms, digital sampling, and filter design.
• The Frameworks: Practical knowledge of EKF, UKF, Lie Group UKF, or Physics-Informed ML is highly advantageous.
• The Stack: Fluency across C++, MATLAB/Mathematica, and Python.
• The Background: Typically a Bachelors, Masters, or PhD in a relevant STEM discipline, paired with few years of recent experience in low-TRL ASP/PNT research.

💼 Why This Role?

This is a high-visibility position where you will bridge the gap between breakthrough R&D, consortia collaboration, and business development. You will shape the technical roadmap, mentor emerging talent, and drive innovation where classical engineering meets the future of AI.

Benefits

• 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

Security Clearance Requirement

Due to the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires Security Clearance (SC). It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant 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.