Job Description

Build a multimodal CNN-LSTM wound trajectory engine from scratch using unique real-world conflict wound data (video and clinical time-series). Government-funded 28-month roadmap; own the technical core end-to-end — multimodal architecture design, XAI integration, edge deployment, federated learning across geographically separated data nodes, and regulatory documentation to UK standards. For the right engineer, broader opportunities across a portfolio of health and med-tech ventures. Requirements: proven CNN and LSTM/Transformer experience on clinical or scientific time-series; multimodal fusion experience (image + structured data) is a strong advantage; hands-on PyTorch, ONNX Runtime, and XAI (SHAP/LIME/Captum); ability to work directly with clinicians. PhD or MSc preferred. UK SC clearance eligibility preferred but not a requirement.