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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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develop the foundational and scalable tools, technology and methods needed to synthesise large sections of human genomes/chromosomes. Through programmable synthesis of genetic material the aim is to unlock
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, and computational humanities. The postholder will lead the curated stream of the project, which involves designing a large corpus of Latin texts, curating it (correction of pre-processed data and corpus
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Christopher Yau (http://cwcyau.github.io ) at the Big Data Institute, University of Oxford. This post will contribute to the development of a new simulation-based pre-training framework for building more robust
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connected large wind energy system dynamic modelling, control and analysis. In particular, the objective of this research programme is to lay the foundations of a new, model and methodology for Advanced wind
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relevant to setting a roadmap for ongoing experiments, as well as recently developed applications of tensor network techniques to large-scale partial differential equations. We are advertising two positions
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member of the ‘Blackholistic’ team (Oxford-Amsterdam-Radboud) which includes relativistic simulations on all scales from black hole to large scale jets, as well as analysis of data from the Event Horizon
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We are seeking an exceptional and highly motivated Senior Research Scientist/ Data Analyst with a passion for tumour immunology and strong expertise in large-scale transcriptomic data analysis
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collaboration with colleagues in the John Radcliffe Hospital and the Oxford Big Data Institute, with the central aim being the development of rapid diagnostics of antimicrobial resistance in clinical samples. You
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project focused on systematically exploring the impact of the exposome on complex disease risk, through the lens of multi-omics data (e.g., genomics, proteomics, metabolomics and biochemistry) from large