Sort by
Refine Your Search
-
refer to the following website for eligibility criteria: https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/physics-and-astronomy-mphil-phd . The studentship will cover university fees
-
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
-
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
-
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
-
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
-
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
-
-scale metagenomic assembly and genome recovery • Comparative genomics and molecular evolution • Machine-learning-based protein prediction • Data integration, bioinformatics and phylogenetics • Scientific
-
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...
-
Develop an active learning-driven platform for compound selection and optimisation Integrate robotic sample preparation, automated data acquisition, and computational analysis Advance five existing
-
-gradient-driven diffusiophoretic focusing for power-free analyte concentration Integrate nanomaterials and microfluidic components into scalable, user-friendly LFA prototypes Validate device performance