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About the Project A fully funded PhD scholarship is available at UCL Electronic & Electrical Engineering (4 years, home tuition fees covered, stipend provided). Exceptional international candidates
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on Project 1 will become a member of the UCL Doctoral Training Centre (CDT) for Data Intensive Science, which administers the PhD studentship. If you apply to Project 1 please submit, in addition to the above
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Develop an active learning-driven platform for compound selection and optimisation Integrate robotic sample preparation, automated data acquisition, and computational analysis Advance five existing
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culture and in vitro models of mucosal immunity Data analysis using Python and digital image processing These skills are highly transferable to careers in biomedical research, pharmaceutical development
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the synergistic effects of monoclonal antibodies and colistin. Building on extensive preliminary data, the project aims to uncover the mechanisms behind this synergy using advanced biophysical and molecular
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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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, host stress, and yield bottlenecks Data-driven design iteration: Integrate empirical data to refine AI-generated plasmid designs Impact and Outlook: This project will deliver scalable, deployable
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Microfluidics and lateral flow assay engineering Translational diagnostics and AMR-focused assay development Digital image analysis and Python-based data processing The project includes opportunities
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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
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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