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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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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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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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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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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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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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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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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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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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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