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Hybrid Algorithm Lead Researcher
AI in this role
Lead research and development of hybrid AI and physics-informed machine learning algorithms for advanced signal processing and navigation systems.
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:
#LI-DB1
At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here.
We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here.
If this role isn’t quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here.
Join Thales in the UK – Innovate with us and shape the future!
How we rate this
Hybrid Algorithm Lead Researcher at Thales rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used Replicate hands-on?
- Walk me through how you've used C in your day-to-day work.
- What are the limits of MATLAB that you've run into, and how did you work around them?
- What's a project where you used Python hands-on?
- Walk me through how you've used Mathematica in your day-to-day work.
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- List these exact terms on your resume: Replicate, C, MATLAB, Python, and Mathematica. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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