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biomaterials, including tuneable 2D and 3D culture systems, advanced microscopy, and polysome profiling, to study the impact of mechanical cues on ribosome function. In parallel, you will use bioinformatics
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interdisciplinary project, combining molecular biology, immunology, genetics, and advanced bioinformatics, working between the Bateson Centre for Disease Mechanisms, School of Biosciences and the Medical School
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molecular and genetic tools. - Applying amplicon sequencing and bioinformatics to characterise microbial communities. - Using advanced statistics and data analysis to make sense of ecological complexity
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high-throughput screening using genetic and imaging tools. Apply molecular and cellular assays to study inflammatory processes. Analyse integrative omics datasets using bioinformatics and machine
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microbiological culturing, molecular skills, bioinformatics and statistics. The project is flexible and can be guided by the interests of the student. Please apply for this project using this link: https
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area such as health sciences, biomedical data, digital pathology, clinical informatics, bioinformatics, or data-driven research Essential Application Undergraduate degree (or equivalent experience) in a
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immunohistochemistry, microscopy and live cell imaging. Essential Application Experience in image analysis or bioinformatics analysis. Essential Application Knowledge of programming languages, e.g. Python/R, and the
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lab https://sites.google.com/sheffield.ac.uk/lahirilab/) with structural bioinformatics (Chaudhuri lab, https://www.sheffield.ac.uk/biosciences/people/academic-staff/roy-chaudhuri) and plant genetics
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bioinformatics analysis skills Essential Application/Interview Significant leadership experience in neurology teaching and research Essential Application/Interview Proven track record of producing high quality
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A search for pharmacological inhibitors of a cancer-associated adhesion GPCR in the zebrafish embryo
are seeking a motivated student with interests in developmental biology, disease modelling and drug discovery. This interdisciplinary project combines both wet bench work and computational work (bioinformatics