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such as Wildfires. Platforms include Satellite, Aircraft, Drones, Mobile Devices using Optical, LiDAR, Navigation sensors. Highly automated Machine Learning and Geo-AI workflows underpin an intuitive Common
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to support real-time response to Emergency Events such as Wildfires. Platforms include Satellite, Aircraft, Drones, Mobile Devices using Optical, LiDAR, Navigation sensors. Highly automated Machine Learning
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Devices using Optical, LiDAR, Navigation sensors. Highly automated Machine Learning and Geo-AI workflows underpin an intuitive Common Operational Picture to transform real-time data streams into a suite of
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Qualifications -Experience using MATLAB, Python, or other programming languages for operation of FUS systems -Experience developing or operating prototype instrumentation, particularly systems involving high
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ordenador a imagen hiperespectral/multimodal/3D y evaluación con métricas específicas. / - Usage of computer vision and hyperspectral, 3D and multimodal imaging techniques and evaluation with specific
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de técnicas de aprendizaje automático (ML/DL) aplicado a imágenes. / Proven experience in the use of machine learning techniques (ML/DL) applied to images. Experiencia demostrable en el desarrollo de
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machine learning to support early detection and prioritisation of patients at risk of vision loss. The role involves leading PPIE activities to ensure that patient perspectives and lived experiences shape
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, efficiency, and outcomes for some of the most critically ill individuals. About you: As a research assistant on this project you will: Support the optimisation of the BathMat prototype for scalable production
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resources. Integration of regularly updated databases, public and private variant prioritization tools using machine-learning methods, bioinformatics predictors of intronic/UTR variant damage, gene panels
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are particularly interested in individuals who have: Strong background at least two of the following areas: machine learning, natural language processing, large language models and multimodal processing Excellent