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the UK is 26th January 2026. The closing date for applications to project 1 from candidates from the EU who do not have pre-settled status and from Overseas is 9th January 2026. The PhD student working
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of industry and healthcare partners, a rare opportunity to develop a highly sought-after interdisciplinary skill set that is in demand across both academia and industry. Training and Student Development
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learning and machine learning for biological data Sequence and structure analysis of large-scale datasets Functional annotation and evolutionary analysis Collaborative research with experimental virology
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the synergistic effects of monoclonal antibodies and colistin. Building on extensive preliminary data, the project aims to uncover the mechanisms behind this synergy using advanced biophysical and molecular
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-penetrating capabilities Evaluate delivery efficiency in cell-based models mimicking lung and immune tissues Identify structure–function relationships to inform rational design of future mucosal delivery
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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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within a highly collaborative setting, benefiting from access to the UCL Automation Network and cutting-edge facilities for structural and biophysical analysis. The project is well-positioned to deliver
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-scale metagenomic assembly and genome recovery • Comparative genomics and molecular evolution • Machine-learning-based protein prediction • Data integration, bioinformatics and phylogenetics • Scientific
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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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The student will work across UCL Mechanical Engineering and RNOH, benefiting from a collaborative environment and access to state-of-the-art facilities. Research Environment: The project is hosted in