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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Cerebral visual impairment, also known as cortical visual impairment (CVI), is a visual impairment caused by damage...
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a digital format. Computer visions techniques have been recently developed for structural health monitoring of civil structures, including vibration displacement measurements, crack detection and
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, who have joined us from all over the world. Everyone here has a role to play. As a member of our professional staff cohort, you will be actively involved in working towards our vision of a better world
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AI architectures such as Transformers, large language models (LLMs), vision-language models, recurrent neural networks (RNNs), and related techniques. Mathematical maturity: A solid grasp of key
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, for instance, utilise conversational agents, computer vision, mixed reality, wearables etc. Disability, Technology, and Society: Research with a sociological or anthropological focus on the use of bespoke and/or
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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has become a world-class university, driving social and economic impacts through science, technology, and innovation. As a dual-sector university, our vision is for people and technology working
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ultra-efficient lasers and all-optical transistors. Our goal is to uncover the elusive physics of strongly interacting polaritons far from equilibrium, bringing the vision of room-temperature superfluid
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demonstrate suitable experience in computer science, machine learning, robotic vision, or a related field (through a high-quality Honours or Masters degree). The successful candidate must be able to enrol as a
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention