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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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pharmaceutical R&D Application of AI in process development and materials discovery Antimicrobial testing and biological evaluation Workflow integration and data management for self-driven laboratories Project
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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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The project includes opportunities for secondments to partner institutions (e.g. University of Birmingham) and industry collaborators (e.g. Halyon Oral Health, BAM Materials), as well as engagement with the UCL
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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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conference presentation. Research Environment: The project is jointly hosted by UCL Chemistry and the Institute of Structural and Molecular Biology (ISMB), in collaboration with Birkbeck. The student will
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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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Develop an active learning-driven platform for compound selection and optimisation Integrate robotic sample preparation, automated data acquisition, and computational analysis Advance five existing