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<p>This Black History Month, we’re celebrating the Black Internship Programme and its importance for improving representation in data science. Zahra Atta, who joined DARE UK as Public Involvement and Engagement Intern this summer, describes a day in the life as part of the team.</p>
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<p>In the third in our blog series showcasing the DARE UK Sprint Exemplar Projects, Professor Michael Boniface and Dr Laura Carmichael from the University of Southampton discuss learnings from the Privacy Risk Assessment Methodology (PRiAM) project.</p>
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<p>The new sector-wide initiative brings together organisations working with data and statistics to collaborate on establishing and driving forward best practice for public involvement and engagement with data research.</p>
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<p>UK Research and Innovation (UKRI) will soon be opening applications for a series of Driver Projects as part of the DARE UK programme.</p>
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<p>In the second in our blog series showcasing the DARE UK Sprint Exemplar Projects, Professor Elizabeth Sapey and Suzy Gallier from University Hospitals Birmingham discuss how the FED-NET project explored federated analytics as a secure solution to combining datasets for research.</p>
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<p>In the first in a new blog series showcasing the DARE UK Sprint Exemplar Projects, Dr Robert French, Senior Research Fellow at Cardiff University and Co-Principal Investigator of the STEADFAST project, discusses the importance of meaningfully involving young people in research which affects them.</p>
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<p>Today, DARE UK publishes a series of reports detailing the findings of a programme of Sprint Exemplar Projects funded as part of Phase 1 of the programme.</p>
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<p>DARE UK has today (Wednesday 31 August) published a summary of findings and recommendations from Phase 1 of the programme to date, and has secured further funding to October 2023.</p>
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<p>Challenge participants working on solutions aimed at bolstering pandemic response capabilities will be able to engage with DARE UK, alongside others, during the competition.</p>
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<p>The team has developed a draft set of usable recommendations for trusted research environments (TREs) to guard against the additional risks when disclosing trained artificial intelligence (AI) models from TREs.</p>