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Field
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evaluation, policy advocacy, or better understanding the contexts and causes of such abuse. The student will use advanced data science and applied statistics to enable combined analysis of different modes
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collection and analysis relevant to community engagement and innovation (e.g. qualitative methods, user feedback, platform analytics). C7: Self-motivation, initiative, and the ability to work independently and
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You will lead the qualitative work to understand how individuals experienced the intervention and app how it worked. This will directly impact the design and refinement of the intervention, and so
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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on health and use economic methods to evaluate relative costs and benefits. This may include use of health impact assessment methods, statistical analysis of secondary data sources to estimate health impacts
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platelets for transfusion. What’s Involved You’ll be trained in a wide range of cutting-edge techniques, including live-cell and intravital microscopy, image analysis, flow cytometry, and cell culture
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, through specific experimental arrangements during the PhD project. This PhD is fully funded by the University of Manchester as part of their commitment to support a recently successful BBSRC-Arxada award
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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challenges. Our community is made up of 13,000 students, 400 professors and close to 4 500 other staff members working on our vibrant campus in Espoo, Greater Helsinki, Finland. We actively work to ensure our
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discipline Strong quantitative and analytical skills Ability to work independently and manage time effectively Good written and verbal communication skills Motivation to address sustainability and climate