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The post is to contribute towards the creation of an outward facing web user interface, for non-specialists to access census data dating back to 1971, for both common geographies and also bespoke
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an opportunity to gain experience in large-scale primary data collection, community-engaged research, and advanced longitudinal and mixed-method analyses. The fellow will be a key member of an interdisciplinary
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the process of measuring and analyzing high-throughput, multi-dimensional omics data integrating single cell transcriptomics and spatial proteomics of immune cells from CSF and blood as well as human brain
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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economic, social and cultural benefits. For more information please visit: https://www.brunel.ac.uk/about/our-history/home The Department of Computer Science at Brunel where this project will be conducted
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using Large Language Models (LLM) to query and reason geospatial data. The project aims to develop a pilot decision support systems in collaboration with industry partners. The Postdoctoral Research
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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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an ARC South London study on multi-morbidity in children using CPRD data. The ARC South London Children’s and Young person theme is important as many children in south London experience high levels of poor
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the Computational Rare Disease Genomics (CRDG) Team, which is led by Associate Professor Nicky Whiffin and based within the University of Oxford’s Big Data Institute. The CRDG team collectively use
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statistical analyses on large datasets to provide biological insights. Integrates mass spectrometry imaging data with other multimodal imaging techniques (e.g., spatial transcriptomics) for comprehensive