Hybrid Algorithm Lead Researcher

Overview

This is a high‑visibility position where you will bridge the gap between breakthrough R&D, consortia collaboration, and business development. As a Hybrid Algorithm Researcher, you will shape the technical roadmap, mentor emerging talent, and drive innovation where classical engineering meets the future of AI. You will lead low‑TRL research and development in Advanced Signal Processing (ASP) and Position, Navigation & Timing (PNT), fusing physics‑based white‑box methods with machine‑learning black‑box models to build solutions that are robust, explainable, and fast.

Responsibilities

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

Qualifications

• Proven experience implementing hybrid algorithms (classical math+ML) for state estimation, anomaly detection, or information fusion.
• Deep familiarity with time/frequency domains, Fourier transforms, digital sampling, and filter design.
• Practical knowledge of EKF, UKF, Lie Group UKF, or Physics‑Informed ML.
• Fluency in C++, MATLAB/Mathematica, and Python.
• Bachelor’s, Master’s, or PhD in a relevant STEM discipline with few years of recent experience in low‑TRL ASP/PNT research.
• Security Clearance (SC) required prior to commencing employment.

Equal Employment Opportunity

At Thales, we ensure equal opportunities, pay, and working conditions for all employees.

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