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own areas of expertise and interests. You will work on a project funded by the University of Leeds that will utilise a broad range of student education data to understand the relationship between
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, including fitness and health facilities, staff discounts, travel schemes and many more. To find out more about what we can offer you, follow the link to our benefits website. What next - Further information
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and upload the research proposal proforma (see link on the university's website, accessed by the 'Apply' button). Further information can be found here: https://www.ncl.ac.uk/sage/research/fellowships/ .
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sets Apply and, where necessary, further develop, novel machine learning methods utilising cutting edge supervised and unsupervised strategies for interpreting the data and linking to IBD diagnosis in
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rewards, including fitness and health facilities, staff discounts, travel schemes and many more. To find out more about what we can offer you, follow the link to our benefits website. What next - Further
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post is fully funded for 3 years and provides an opportunity to obtain a PhD. The project will enable the candidate to develop unique skills in complex linked data handling, geospatial analysis and
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you to further develop your own areas of expertise and interests. You will work on a project funded by the University of Leeds that will utilise a broad range of student education data to understand
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fidelity. This role will involve a mixed-methods approach, including quantitative and qualitative data collection, fidelity assessment, and economic modelling. The Research Fellow will work closely with
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, with opportunities to build an international research portfolio. The post holder will work on developing and testing study design and data analysis methods, particularly related to cluster randomised
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fitness and health facilities, staff discounts, travel schemes and many more. To find out more about what we can offer you, follow the link to our benefits website Further information is available in