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work to generate high fidelity models of ice crystal icing shedding, verifying tools using a wealth of unique experimental validation data generated by researchers at the Oxford Thermofluids Institute
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computations emerge from cortex-wide neural dynamics across species. The PDRA will contribute primarily to developing and analysing Cortically-Embedded Recurrent Neural Networks (CERNNs) that simulate large
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in the use of genomic data in public health – access to big data sets, the technology to analyse these data, and the knowledge to interpret the results. In this role, you will develop, optimise, and
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established and emerging bioinformatics, statistical modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics
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assistive technologies and contributing to high-quality publications in leading HCI venues such as ACM CHI and ASSETS. The researcher will have the opportunity to be involved in a large number of exciting
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relevant PhD/DPhil in socio-legal studies, political science, sociology, human rights, or a related field together with relevant experience; experience in managing large-scale data collection projects and
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A Research Associate post is available at Lancaster to work on the upgrade of the ATLAS experiment at the CERN Large Hadron Collider. The post will focus on computing and software upgrade program of
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demonstrable experience in the analysis of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single-cell sequencing, gene
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examines gambling behaviour and ways to address gambling harm. Two types of data will be employed. The first is publicly available data from national surveys and from the Gambling Commission, such as the
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studies (GWAS), fine-mapping, colocalisation, polygenic risk scoring, and Mendelian Randomisation; and (ii) deep phenotyping of multi-modal cardiovascular imaging (MRI, CT, echocardiography) from large