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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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. 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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challenging. This project aims to develop an ultrasound-assisted nanoparticle-based drug delivery system for targeted, controlled release of antimicrobials within these hard-to-reach oral microenvironments. By
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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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implant failure and limb amputation. Current antimicrobial coatings often rely on antibiotics or metallic agents, which may contribute to antimicrobial resistance (AMR) or cytotoxicity. This project aims
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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
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on recent advances in recombinant RNAP production, cryo-EM structural elucidation, and fragment-based screening, the project will integrate fluorine-based NMR spectroscopy with active learning algorithms and
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together I) microfluidic/flow-based nanoparticle synthesis, which underpins modern nanoparticle drug delivery systems including the Pfizer–BioNTech COVID-19 vaccine, together with II) high-throughput
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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