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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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modeling. The role involves developing and implementing computational methods to integrate single-cell and spatial transcriptomics, proteomics, metabolomics, and metallomics data. Using advanced techniques
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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of routinely collected maternity data and can be linked with other health datasets in south London such as the records of the local mental health Trust using the Clinical Record Interactive Search