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diagnostics, empirical antibiotic use is common, exacerbating resistance. This project aims to develop a next-generation lateral flow assay (LFA) platform for rapid, ultrasensitive detection of RTI pathogens
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propagate through bacterial communities while deactivating AMR genes. However, current designs are limited by scalability and complexity. This project aims to overcome these limitations by integrating large
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. Approach and Methods: Apply deep learning-based modelling and clustering to analyse a curated dataset of hundreds of thousands of UL-CDR sequences Characterise sequence–structure relationships and structural
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transformations at such interfaces, and how they are influenced by external electric fields and electrolyte composition. Access to high performance computing facilities including GPU clusters will be provided
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management and coordination within a multidisciplinary environment Scientific writing and effective communication within a multidisciplinary environment Networking, career development, and professional self
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Eastman Dental Institute. Research Environment: The student will join a vibrant, multidisciplinary research community within UCL’s Mechanical and Chemical Engineering departments. The project is supported
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reasoning and interdisciplinary communication Research Environment The project will be hosted in two collaborative, interdisciplinary labs with expertise in: Evolutionary microbial genomics and phylogenetics
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Supervisors: Dr Julia Rho – Rho Group Website Dr Pratik Gurnani Abstract: Vaccines are a cornerstone of infectious disease prevention and a key strategy in reducing antimicrobial resistance (AMR). While mRNA vaccines have demonstrated rapid development and high efficacy, current formulations...
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disinfectants. With antimicrobial resistance (AMR) on the rise, there is an urgent need for non-antibiotic strategies to prevent and control biofilm formation on medical devices. This PhD project proposes a novel
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for microbiology and screening assays, MRC and Wellcome-funded. Both labs promote an open, collaborative culture and have a strong track record of PhD supervision. Desirable Prior Experience Some prior experience in