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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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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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. road, power distribution). This project will develop new insights into what drives flooding and extreme wind to co-occur on timescales from (sub-)daily to seasonal. Our recent work suggests that
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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of how a changing climate shapes planet Earth. Our hypotheses, which you will refine and test are: 1. Bedrock channel incision in Tenerife is locally controlled by the climatic regime. 2. River profiles
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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minimum English language requirements. Further details are available on the International website . Funding information: This PhD project is jointly funded by EPSRC (via the Industrial Doctoral Landscape
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should be made online . Under programme name, select School of Architecture, Building and Civil Engineering. Please quote the advert reference FCDT-26-LU9 in your application. This PhD is being advertised
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Plants and trees are vital to the UK’s economy, ecosystems, and climate goals, providing an estimated £15.7 billion annually in environmental and economic value and playing a crucial role in
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-26-LU4 in your application. This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen at https