20 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ETH-Zürich" Fellowship positions at University of London
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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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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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of data collectors; and working with multi-country teams. Availability and willingness to travel abroad, including to Lebanon, are essential. Further particulars are included in the job description. The
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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
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linked EHR data. This project explores socioeconomic and ethnic inequalities in respiratory virus transmission and their impact on GP services in winter and whether these pressures are evenly distributed
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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 will not be considered. An answer to any
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into the wider community of established scholars within the British history field. For a full role profile, please refer to the job description below. Further information To be considered for this opportunity
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, focus groups, observation and documentary analysis, and will lead on the analysis and synthesis of qualitative data using systems evaluation frameworks. The role requires an excellent understanding
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. Please provide 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
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at LSHTM. The post-holder must have a postgraduate degree in a relevant topic (ideally Medical Statistics or equivalent) and relevant experience in using regression models for data analysis and statistical