21 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Here We Are" Fellowship research jobs at University of London
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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data, working to a preregistered Statistical Analysis Plan. The research applies target trial emulation, to generate robust and policy-relevant evidence. Working closely with the research team
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is a research project focusing on transforming urban food systems for planetary and population health. The postholders will conduct data analysis and prepare papers for publication using already
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estimations in humanitarian and public health contexts by developing reproducible, multilingual workflows for social media analysis, building data pipelines in R/Python, and creating open-source tools for text
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one or more paragraphs addressing each criterion. The supporting statement is an essential part of the selection process and thus a failure to provide this information will mean that the application
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of implementation analysis). This will include reviewing data from a feasibility study, identifying supplementary data needs, and developing tools for costing in a full trial. The postholder will also contribute
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, proven expertise in trypanosome genetic manipulation and functional analysis, as evidenced by first name authorship, proven expertise in the generation and analysis of proteomic and RNAseq data, as
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endemic countries. We are seeking to appoint a Research Fellow to join a research programme that applies advanced bioinformatic, statistical, and population genomic approaches to large-scale sequencing data
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B microarray patch (MAP) technology for the delivery of timely birth doses of the hepatitis B vaccine to prevent vertical transmission of hepatitis B. The post-holder is expected to use data from
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. The study integrates clinical, microbiological, and data science approaches to generate evidence and tools for safer, more targeted infection management in hospitalised newborns. Key output involves leading