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Field
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In this role you will develop cutting edge AI approaches to help researchers identify scientific information in historical manuscripts. Specifically, working with the Royal Horticultural Society
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the Lymphovascular Research group collaborating with computational, clinical and laboratory scientists. The post holder will support the group by analysing genomic data to identify and characterise genes underlying
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through all stages including implementation and supporting sites in recruitment, regulatory approvals, data collection and integrity, data presentation and working with translational samples. The post is
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will work across four Work Packages, developing partnerships with schools, project partners and other groups, and using mixed methods to collect and analyse new data and synthesize existing data sets
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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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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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) to provide benchmark data as well as the quantum technology gravity gradient sensor. This involves close liaison with colleagues across campus, especially as part of QuSIT, partner institutions, project
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first-time applicants might need to qualify for salary concessions. For more information, please visit the Government’s Skilled Worker visa page. For research and academic posts, we will consider
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this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information, please visit the Government’s
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team members to ensure all project deliverables are met. Accumulate data from Co-PIs for quarterly, annual, or final progress reports Schedule meetings with co-PIs, collaborators on-site or off-site