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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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data science, computer science, bioinformatics, structural biology, or a related area, and have experience in image analysis, machine learning and/or scientific computing. Informal inquiries should be
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environment at Duke is ideal for our translational research efforts. Applicants must : 1. Hold a PhD with relevant skillsets in programming (including Python) and machine learning methods for image