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models. These models will leverage both imaging data and corresponding radiology reports during training to build comprehensive representations that capture the rich, complementary information contained in
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of thousands of individuals, large-scale single-cell data from primary human tissues, spatial transcriptomic data, and experimental genomic screens. The postholder will join a multidisciplinary team based in
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, BLIP), fine-tuning large language models for clinical NLP, and self-supervised contrastive learning—the models will learn to effectively combine visual and textual information. By developing
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to automate scientific discovery in both the natural and social sciences. The postholder will contribute to one or more of the following strands: • Foundational work on large-scale/foundation models and
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. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
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foundational theory of how large ML systems can be regularised to have dramatically fewer trainable parameters without sacrificing accuracy by analysing the use of low-dimensional building blocks Implicit
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comfort and would be interested in a fixed term role to support a large project looking at developing outdoor thermal comfort models for children? If so, we would welcome your application to this full-time
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large, multi-site human cohorts in Europe. The successful candidate will oversee the collection, processing and analysis of microbiome samples, ensuring harmonised protocols, high-quality data generation
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of therapeutic genomics, leveraging large-scale functional genomic datasets and cutting-edge computational resources, including university HPC clusters and AWS. The post-holder will advise colleagues on data
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researchers to join the laboratories of Prof Michael Browning and Prof Jacinta O’Shea, to work on a large-scale project, sponsored by a Wellcome Mental Health Award. About the Role The posts are funded for 2