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. ¿ Study design, protocol development and laboratory diet planning. ¿ Leading on participant recruitment, data collection and analysis. ¿ Supervising a graduate level research assistant
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) Knowledge of intersectionality-informed approaches to research including in data collection and analysis. Good collaboration skills, including with people with lived experiences, other research and academic
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applicant should have prior experience in data analysis, data visualization, and preferably the development of interactive web-applications through approaches such as Bokeh, Shiny, Taipy, Streamlit etc
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new data will be linked with information from samples previously collected during pregnancy, there will also be opportunities to be involved with analysis of multi-omic data to study mechanisms
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collaboration with statistical physicists for data analysis and experimental design. The Associate is expected to generate breakthrough ideas in the assigned area of research, as well as to carry out research in
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detailed T-cell phenotyping and functional assays • Conduct mechanistic studies using molecular and cellular immunology techniques • Contribute to data analysis, presentation, and publication
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-scale data analysis, and systems modelling. The post holder will play an integral role in experimental design, sequencing, data interpretation, manuscript preparation, project coordination, and the
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on tunable hydrogels and analysis through quantitative microscopy techniques. The postholder will further collaborate with project partners to establish a framework of mechanosensation and mechanical memory
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planning and conducting speech experiments and data collection, and highly skilled in linguistic, acoustic and quantitative data analysis. With a strong research record, they will have the ability to manage
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing