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impacts and suboptimal decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport
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of diverse clinical scans and the anatomical structure of the heart. The model can be fine-tuned for different clinical tasks without retraining the entire network, enabling an agile workflow for performing
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. This position provides a unique chance for a highly motivated researcher to contribute meaningfully to innovative computational modelling focused on achieving net-zero goals. Number Of Awards 1 Start Date 1st
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) is key to unlocking deep-water renewable energy and achieving the global Net Zero targets. However, dynamic power cables that connect floating wind turbines to the seabed remain one of the challenging
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). Additional project costs will also be provided. Overview Offshore Floating Wind (OFW) is key to unlocking deep-water renewable energy and achieving the global Net Zero targets. However, dynamic power cables
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coordination capabilities essential for operations in complex urban environments. With advancements in 5G mobile networks, Artificial Intelligence (AI)-driven navigation, Internet of Things (IoT) connectivity
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for the ‘Course Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study You will then need to provide the following
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical deep neural networks), multimodal vision and
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instrumentation of the structure, whilst effective, can be logistically expensive to implement for the entire network. To address these challenges, the project aims to develop a novel, population-based indirect
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Variability Lab (led by Professor Emily Farran) and the Cerebra Network (co-led by Dr Moss). They will collaborate with PhD, Clinical Doctoral, Masters and undergraduate students engaged in neurodevelopmental