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Field
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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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Students Project Description The NetZero Futures (NZF) Doctoral Landscape Award is a fully funded EPSRC studentship with the Royal College of Art. The strategic vision of NZF unites RCA-wide Art and Design
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principles, lab measurement, computer vision and ArcGIS, potential fieldwork and UAV flying training. Person specification Experience and/or enthusiastic interest in one or more of the following areas
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in AI. Previous publication record in relevant fields: AI, machine learning, computer vision, etc. Previous successful project on a relevant topic. Good knowledge of statistics, probability
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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of mission design, manufacturing, operations, and disposal. This PhD project aims to advance sustainable space operations by developing a holistic lifecycle assessment framework and computational tool
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electronics, enabling spontaneous gaits powered by a single onboard pressure source. The project’s vision is to establish embodied oscillator intelligence, where locomotion arises from the physics of coupled
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Students Project Description The NetZero Futures (NZF) Doctoral Landscape Award is a fully funded EPSRC studentship with the Royal College of Art. The strategic vision of NZF unites RCA-wide Art and Design
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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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