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Field
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-driven shifts in species distributions. Currently, barnacles and other species are manually counted from over 3,000 images each year, which is time-consuming and prone to human error. This project will
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training platform. You will gain hands-on experience in cutting-edge plant ecophysiology techniques such as chlorophyll fluorescence, gas exchange (using LICOR systems) and thermal imaging, to assess plant
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
for automated, data-driven diagnostics, integrating AI with high-resolution imaging and sensing offers a transformative solution. AI models can learn to recognize subtle damage patterns, enabling faster, more
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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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degree and/or relevant previous experience with one or more of: brain imaging (e.g., MRI, EEG, MEG) and/or brain stimulation (e.g., TMS, tACS, TIS). The PhDs would start in October 2025 and are fully
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primary research aim will be to explore how the geometry of data can help build better uncertainty-quantifying models, particularly for complex data types like molecules and images. However, other research
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, and epibenthic biodiversity. The project will build on a working prototype, the Neural Network Enhanced Marine Observation system, a low-cost, shallow-water, edge-AI-enabled spatial camera system
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rest, will be combined with detailed in vivo human physiology techniques in healthy volunteers. Methods may include stable isotope tracers, blood and muscle biopsies, imaging (ultrasound, MRI, DXA), and
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forms of artistic recreation across cultures and time. Where words and images live on in successive iterations, the project will chart varying attitudes to their themes and trace genealogies of cultural
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financial economics. You will work at the frontier of interdisciplinary research, using high-resolution flood models alongside property data to build a dynamic picture of where flood hazards are concentrated