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Field
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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for appointment at Grade 7 with a salary range of £39,424- £47,779 per annum with amended duties and responsibilities. About us The MMM Unit is based at the Big Data Institute and John Radcliffe Hospital. We work
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, as well as for their babies. You will work with large, complex datasets from national surveys and routinely collected health data to support impactful research. You will manage your own research
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on an exciting Wellcome-Trust funded project. The research focuses on decoding neural representations across dynamic brain states through advanced computational analysis of large-scale neural recordings. What you
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will use large genomics databases such as the UK Biobank, a collection of 500,000 individuals including genetic and healthcare records. The project is a data analysis project – from day to day you will
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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rapid economic and social change. Controlled cross-cultural studies will be informed by locally-led participatory research. Two large scale trials are underway/in preparation in Colombia and Nicaragua
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by