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language model (LLM)-based genome design tools with bioprocess engineering to create next-generation therapeutic conjugative plasmids. These engineered plasmids will be optimised for industrial-scale
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, numerical methods, molecular biology methods (e.g. cloning, PCR) and bacterial plasmid mating. How to apply This project is offered as part of the Centre for Doctoral Training in Engineering Solutions
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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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(SONATA, EP/V028626/1) and brings together expertise in microfluidics, fluid dynamics, nanoparticle engineering, and dental microbiology. Approach and Methods: Engineer in vitro models of bacterial biofilm
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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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-pharmacological antifungal therapies. Approach and Methods: Develop and optimise laboratory models of fungal growth and resistance. Investigate how environmental stress factors (e.g. osmotic and nutrient stress
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). Design and fabricate patterned surfaces optimised for enzyme immobilisation. Assess synergistic antibiofilm efficacy under static and dynamic (flow-based) biofilm models. Apply advanced microscopy, protein