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techniques. The findings will lay the groundwork for clinical application and contribute to the development of targeted therapies for resistant bacterial infections. Approach and Methods Atomic force
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Methods Soft lithography and microfabrication to create defined surface landscapes. • Mating assays between resistant and sensitive Enterobacteriaceae strains. • Live-cell imaging and fluorescent plasmid
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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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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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Abstract: Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a leading contributor to global antimicrobial resistance (AMR). Non-tuberculous mycobacteria (NTM) also pose serious
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labs The project offers access to GPU-enabled HPC clusters, high-end workstations, and a collaborative, interdisciplinary environment. The student will develop a versatile skill set applicable to careers
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within a highly collaborative setting, benefiting from access to the UCL Automation Network and cutting-edge facilities for structural and biophysical analysis. The project is well-positioned to deliver
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of industry and healthcare partners, a rare opportunity to develop a highly sought-after interdisciplinary skill set that is in demand across both academia and industry. Training and Student Development
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, an application to the DTC by the above deadline following the instructions given here : Informal enquiries regarding both positions can be made to Jochen Blumberger by email, j.blumberger@ucl.ac.uk .