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their pandemic potential and classification as bioweapons. This project aims to develop a machine learning-accelerated NMR platform for the discovery of high-affinity inhibitors targeting viral RNAPs. Building
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: Machine Learning Molecular Dynamics. The project involves the development and application of machine learning methods that enable a major boost of the time and length scales accessible to ab-initio/first
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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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-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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interest are also welcome. Motivation to learn about nanoparticle formulation, microfluidics, or data analysis is highly valued. Motivation to work in AMR and nanomedicine and to learn how AI can guide
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Supervisors: Dr Julia Rho – Rho Group Website Dr Pratik Gurnani Abstract: Vaccines are a cornerstone of infectious disease prevention and a key strategy in reducing antimicrobial resistance (AMR). While mRNA vaccines have demonstrated rapid development and high efficacy, current formulations...
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Supervisors: Prof Stavroula Balabani Prof Panagiota Angeli Abstract: Oral biofilms are a major cause of dental and periodontal diseases, including endodontic infections and dental caries the most prevalent noncommunicable disease globally. The confined and complex architecture of the oral...
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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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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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Supervisors: Prof Manish Tiwari Prof Shervanthi Homer-Vanniasinkam Clinical Partner: The Royal National Orthopaedic Hospital (RNOH) Collaborator: Dr. Priya Mandal – UCL Mechanical Engineering Abstract: Medical device-associated infections (MDAIs) are a major clinical and economic burden,...