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Field
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more via our website. Your next career opportunity You will lead computational analyses of single-cell and spatial transcriptomics data in abnormal uterine bleeding research. You will collaborate closely
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analyses of single-cell and spatial transcriptomics data in abnormal uterine bleeding research. You will collaborate closely with US-based clinicians and experimentalists to translate discoveries
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and single-cell omics (transcriptomics, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data. Independently carry out computational and bioinformatics analysis for large-scale spatial
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, and hypothesis generation. Integrate transcriptomic, epigenomic, spatial transcriptomic, and other multi-omics datasets. Perform gene regulatory network, transcription factor, pathway, and cell-state
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early metabolomic disruptions, followed by the genetic and biochemical dissection of the mechanisms underlying these alterations. The project takes advantage of recent transcriptomic and imaging data
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the field of pulmonary fibrosis using animal and primary cell culture models, single-cell, and spatial transcriptomics approaches. The successful candidate will be expected to build a publication record in
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neurons and breast cancer organoids, together with clinical tissue material, to investigate cancer-nerve contact sites using multiplexed immunofluorescence, single-cell and single-nucleus transcriptomics
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, including analysis of genomic/metagenomic/transcriptomic data, would be an advantage. Experience with R, Python, Linux/Unix, sequence-analysis tools, or biological databases is an advantage. Good analytical
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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development and human diseases, such as neurological disorder, immunology, and cancer. Utilize biochemistry, molecular biology, CRISPR-based genomic screen, single-cell transcriptomics, and genetically modified