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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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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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excited by methodological innovation and real‑world impact. You will hold a PhD in a quantitative discipline such as infectious disease modelling, statistics, mathematical epidemiology, data science, or a
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interpretation of experimental data; Teamworking experience; Publication record commensurate with career stage. Demonstrate proficiency with data analysis tools (e.g., Python/Matlab/Origin). Have the ability
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collaborators, you will conduct analyses of the Swiss HIV Cohort Study (SHCS) data to identify and characterise underserved populations who could benefit from PrEP. You will use intersectional approaches
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for the analysis of ONT data are expected. The successful applicant will work in the team of the Joint Microbiome Facility of the Medical Univeristy of Vienna and the Univeristy of Vienna (JMF), and support Centre
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use the data to inform and amend the recruitment strategy as required. The postholder will also conduct interviews with participants after the prosthesis is fitted to understand engagement and
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Extract and synthesise data from published studies Contribute to the analysis and synthesis of international evidence on research impact frameworks and indicators Assist in the preparation of academic
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auditing, explainable AI (XAI) analysis and data-flow mapping, on welfare-AI systems in the UK, Netherlands and Sweden, contributing to comparative insights and high-quality project outputs. They will
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care