4 of 4 Sensor Fusion Jobs in Essex

ML Research Scientist to join its growing Data and Decision Support capability. This role focuses on developing advanced algorithms and machine learning solutions for sequential (time-series) data , including sensor signals, RF, radar, sonar, and related applications. You'll work at the forefront of AI/ML innovation , contributing to real-world projects in defence, security, space, and commercial … and deliver research programmes independently and in teams Desirable Experience (one or more of the following): RF communications or electronic warfare (EW) Radar or acoustic (e.g., sonar) signal processing Sensor fusion and multi-sensor tracking Distributed sensing systems or edge ML Autonomy and human-machine teaming Space-domain awareness (SDA) Navigation, positioning, and timing systems Behavioural analytics More ❯

cost, schedule & quality implications Domain experience any of the following specialisms; Telecommunications, RF, Electronic Warfare, Electro-Optics, Air/Land/Sea sub-system Platform Integration, Data Distribution Services, Sensor Fusion, AI/Machine Learning Practitioner level ability using Model Driven Engineering tool e.g. Cameo Systems Modeler, Matlab, Simulink, DOORS (classic) This is not an exhaustive list, and More ❯

with frameworks like PyTorch, TensorFlow, or scikit-learn. Proven ability to communicate complex results to technical and non-technical audiences. Desirable: experience in areas such as radar, EW, RF, sensor fusion, autonomy, or signal processing. Role: AI Data Science & ML Researcher Salary: £60,000 - £70,000 Additional Package: 10% Bonus, Extensive Benefits Package Location: Chelmsford Want to hear More ❯

problems. The role involves leading high-value research initiatives for defence, security, and commercial customers. You will work across multiple domains including radar, RF, acoustic signal processing, autonomy, and sensor fusion. Key Requirements: PhD or equivalent experience in AI/ML or statistical signal processing Strong Python programming and use of ML libraries (e.g., TensorFlow, PyTorch) Demonstrated experience with More ❯