51 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" "UCL" "UCL" "UCL" PhD research jobs in United Kingdom
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to better predict incident disease from high-dimensional genetic and non-genetic data, quantification of trait heterogeneity and asymmetry from imaging data, leveraging biobank genetic and prescription data
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) to analyse results, gather relevant data for modelling, and ensure accurate data collection Analyse data, interpret resultsand compile findings into detailed reports for regular project team meetings
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group, including PhD and MSc and honours project students. You will also be heavily involved with data analysis and writing up manuscripts. Please see the below 'Job Description' for further details
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‑bounded turbulence. This short, intensive 9‑month position offers an exciting opportunity to advance fundamental turbulence research using DNS/LES and data-driven optimisation techniques. In this role, you
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of Singapore's research and innovation ecosystem and aims to support the development of a sustainable, climate-resilient, and healthy city through data-driven design and policy-relevant research. The programme
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considered for Research Assistant. Strong programming expertise in Python and C++, with experience developing real-time robotic and AI systems. Experience in deep learning and computer vision, including
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | about 2 months ago
function in the Safety and Surveillance group. Within a week of working here, your day could look like this: help shape the UK Government’s premier data-driven research service. You will participate in and
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Development”, funded by an ERC/UKRI Starting Grant 2023. The project will leverage micro-level data from multiple countries and novel theoretical frameworks to shed light on how the accumulation and utilization
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quality of this evidence to ensure it is sufficiently robust to help Welsh policy makers. For further information, please see this blog which takes stock of the Apprenticeship scheme and this article
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variation in breast cancer susceptibility using whole genome sequencing data”. This project will investigate the contribution of rare non‑coding regulatory variants, including those in enhancers, promoters