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synthesis and formulation platforms, the project will generate and screen a diverse library of polymers optimised for mucosal delivery. The resulting delivery systems could enable next-generation vaccines
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. Interested candidates may want to take a look at our recent work on machine learning molecular dynamics: https://www.nature.com/articles/s41467-024-52491-3 Project 2: Non-adiabatic Molecular Dynamics
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Supervisors: Dr. Maximilian Besenhard Dr. Maryam Parhizkar Abstract: Antimicrobial peptides (AMPs) are natural molecules produced by the immune system and represent one of the most promising avenues
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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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in academia, biotech, and pharmaceutical R&D. Research Environment: The Orengo and Lasso labs provide a dynamic, inclusive, and multidisciplinary research environment at the intersection
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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
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enzymes. Mapping bacterial defence systems to infer predictive features of co-evolutionary dynamics. Impact and Outlook This project will: • Advance understanding of microbial co-evolution. • Deliver a
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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
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: Produce recombinant viral RNAP transcription complexes in insect cells Functionally characterise RNAP activity and validate assay systems Screen fragment libraries using fluorine-based NMR spectroscopy
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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