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analyse large scale job application data from employers using quantitative methods. Findings from the analysis will be written up in a project report, separate reports to employers, and in academic journal
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/drc/ ). About the role The role will contribute to on-going research at the UCL Hawkes Institute to develop advances in computational modelling of neurodegenerative disease, machine learning, and big
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of inherited neuromuscular diseases in a large and diverse research cohort. In addition to your research project, you will attend regular clinical meetings to discuss clinical and genetic results. You will also
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applications for a PhD-student (m/f/d; 65%, 3 years in first instance) to work on a large-scale €6m multi-site Wellcome-funded project. This position is suited for researchers who have finished or are about to
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biology, bioinformatics, genomics, statistics, physics, or a related quantitative field Demonstrated ability to analyse large-scale sequencing data using R, Python or equivalent A self-motivated team player
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immunotherapies for childhood brain tumours. The successful applicant will join an existing team of researchers with a focus in this area. The successful candidate will initiate a large barcoding initiative and
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clinical data from large cohort studies on immune-mediated inflammatory diseases including psoriasis and rheumatoid arthritis. The PDRA will lead on research across all three objectives, taking first
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to the PhD programme, including a project plan outline for the training plan, must be submitted no later than three months after the date of commencement. PLEASE NOTE: For detailed information about what the
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of the shipping system, shipping big data, and social science analysis of the policy and commercial structure of the shipping system. The research group’s multi-disciplinary work is underpinned by
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, using genomic and clinical data from large cohort studies on immune-mediated inflammatory diseases including psoriasis and rheumatoid arthritis. The PDRA will lead on research across all three objectives