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investigate the wildlife connectivity potential of tree-based agricultural systems, combining biodiversity surveys, animal movement data, landscape modelling and remote sensing to understand how trees within
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depths and water sources? Can aboveground tree morphology be used to predict belowground water use and root-zone water dynamics? Can mechanistic models be used to predict how different tree-based farming
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demonstration of a DNA-based stack data structure and recent advances in optimisation for DNA nanotechnology, the project will design, model, implement, and experimentally validate novel molecular data structures
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biology approaches to identify transcriptional networks and signalling pathways controlling cardiovascular development. Using novel datasets generated from mouse models of congenital heart defects, the
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biology approaches to identify transcriptional networks and signalling pathways controlling cardiovascular development. Using novel datasets generated from mouse models of congenital heart defects, the
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. Enforcing these is hard when the data, the model, and the rules belong to different parties, none of whom can hand over what they hold. Privacy-preserving AI protects data and models but not rules, while
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intensification, dynamic operation, and resource recovery. The project combines modelling, pilot-scale experimentation, and techno-economic assessment to establish MECs as viable unit operations within next
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, machine learning and Quantitative Microbial Risk Assessment Microsimulation modelling, generating evidence directly relevant to national food safety policy. You will join a PhD student cohort with NIHR
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implementations face signal delay and stability constraints. We will combine synthetic biology, microfluidics and computational modelling to address these key challenges. Building on our microfluidics set-up, we
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will gain: Data analysis, modelling, and technoeconomic assessment skills Professional development in communication, leadership, and industrial collaboration Access to a strong network of industrial