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Field
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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The project: The focus of this project is on the novel and exciting concept of multi-rotor wind turbines; a new design paradigm for wind energy, that is attracting an increasing amount of attention
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decision processes. Use the CARLA simulation platform to generate DCD-style data in high-risk or ambiguous driving scenarios. Build a proof-of-concept verification pipeline that maps DCD outputs
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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Atmospheric rivers are narrow bands of strong vertically integrated water vapour transport (IVT), conjuring the image of a river in the sky. This phenomenon has been studied extensively in relation
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for computer, lab, and fieldwork costs necessary for you to conduct your research. There is also a conference budget of £2,000 and individual Training Budget of £1,000 for specialist training Project Aims and
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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stress analysis, manufacturing, hands-on oriented, digital image correlation, Abaqus, scripting How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement
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Project Supervisor - Dr Jonathan Kirby The field of complex numbers is in many ways the most elegant and important example of a mathematical structure in model theory. It has been the prototype