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interests, you will have the opportunity to work with: High‑throughput functional genomics: pooled CRISPR and base‑editing screens, barcoded overexpression libraries, massively parallel reporter assays
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scale DNA libraries with generative synthesis models, translating in silico predictions into physical gene libraries for experimental testing. Building and evaluating probabilistic deep learning models
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of mRNA or expression libraries lead in vivo studies, including delivery, tissue collection, phenotyping, and downstream analysis integrate and analyse multimodal datasets using Python or R to inform
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interpretation; Preparing numerical and graphical summaries (visualizations) using relevant software and libraries for dissemination to both scientific and broader audiences; Assisting with grant applications
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integration, selection and automated use by the bot: (1) We propose to identify and implement a library of tools to perform important generic tasks on the knowledge graph including: name-entity recognition