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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships
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screens, focusing on the relationship between regulatory elements and gene expression. Train and develop sequence-based deep neural networks to predict gene expression outcomes. Document findings and
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a relaxed and diverse atmosphere defined by constructive thought exchange. Opportunities to learn about model systems of disease, advanced microscopy, genetic engineering, new sequencing techniques
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problem solving strategies used in nature and to ground these ideas by fostering deep collaborations with experimental biologists. Most recently, we have been interested in neural circuit computation and