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for antibiotic prescription. Novel, rapid, point-of-care, precise and easily interpreted diagnostic tools are required to tackle this challenge. Direct sequencing of nucleic acids from patient samples can be rapid
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The project: Motivation The development of hydrogen energy technologies is central to the UK government's ten-point plan for a green industrial revolution, targeting a 40% reduction in gas
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for antibiotic prescription. Novel, rapid, point-of-care, precise and easily interpreted diagnostic tools are required to tackle this challenge. Direct sequencing of nucleic acids from patient samples can be rapid
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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mathematics are welcome to apply. Hands-on experience in optical laboratories will be a plus. How to apply: Please visit the UCL i4health CDT webpage linked above for instructions on the application process. In
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new sustainable femtosecond laser nanomanufacturing process to overcome the challenges of atomic sale precision, feature size and defects rates for quantum dots. In this project, molecular dynamics
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components with applications in the transport, catalysis and bioengineering industries. The research will focus on wet chemical processes and the study of chemical reactions on the component's surface. We will
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metagenomics, host transcriptomics, and clinical metadata. Training will be provided in ONT data processing, differential expression and abundance analysis, and bulk or single-cell RNA-seq. The project will use
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with participants to deliver measures concerning people’s experiences of the diagnostic process, their access to services and their general well-being and life quality. The positions are ideal for people
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non-random, with specific motifs within the glycan chains defining binding sites for critical signalling and structural molecules. Unravelling the ways in which these motifs are encoded into GAGs by