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Field
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Nanopore sequencing, ChIP-seq, and Hi-C, to probe plant genomes and centromeres. The project will involve both wet-lab based functional genomics approaches, together with dry-lab based bioinformatics
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bioinformatic tools and focused on clear interpretation and communication of this data. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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the challenges of dynamic sensor networks for sleep management. Through the joint supervision between multiple disciplines, the student will be offered a unique opportunity to develop a robust personal portfolio
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metrics during both standard operation (primarily governed by system reliability) and extreme events (primarily governed by robustness and restoration). This will be achieved by building on previous
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relevant to multiple applications, including small aircraft, drones, turbines, and other systems reliant on efficient fluid flow around foils. The project offers a unique opportunity to gain experience in
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functioning [1]. Building on these insights, you will compile and standardise datasets of collective movement and collect new data from multiple species of freshwater fish. From these data, you will identify
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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small number of crops, undermines the sustainability and resilience of land use. However, we do not have a good understanding of how land could be used for multiple purposes whilst being sustainable and
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Project Background: Why some people with multiple sclerosis (MS) experience faster changes in brain structures (neurodegeneration) than others? What genetic associations with brain regional