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studies visuo-semantic cognition combining cognitive science, neuroscience, and computational modelling. We combine experimental behavioural tasks, brain imaging (fMRI and M/EEG), and, through
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that suppress resistance gene transfer. Combining biophysics, microbiology, and materials science, the project will generate insights into how physical environments can be harnessed to control AMR. Approach and
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project aims to develop state-of-the-art computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the
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PhD Studentship: Nanopore Technology for Rapid and Accurate Measurement of Antibiotic Concentrations
samples. Nanopore technology, which detects molecules via changes in ionic current as they pass through nanometer-scale pores, has revolutionised nucleic acid sequencing and holds untapped potential
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within the Institute of Health Informatics. The studentships will commence from Feb 2026. About the project Successful applicants will work with the programme coordinator to identify a project and a
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Angeloudis Assistant Supervisor: Professor Lindsay Beevers Eligibility Minimum entry qualification: An Honours degree at 2:1 or above (or International equivalent) in Engineering, Oceanography, Computational
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communication, and applied security research. Applicants are expected to hold (or be close to completing) a minimum of an upper second-class undergraduate honours degree (or equivalent) in Computer Science
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Training in Engineering Solutions for Antimicrobial Resistance. Further details about the CDT and programme can be found at AMR CDT website Applications should be submitted by 12th January 2026.
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are fundamentally limited by a "one model for one task" design philosophy. This approach incurs prohibitive engineering costs and yields brittle solutions with poor generalisation to new network conditions, trapping
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Student Development The successful applicant will gain expertise in: Biophysical imaging (AFM, microscopy) Microbiology and molecular biology RNA sequencing and data analysis Interdisciplinary collaboration