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Field
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to work collaboratively to integrate microbial phenotypic data (e.g., fluxomics, transcriptomics, proteomics, metabolomics) into quantitative computational models capable of predicting and explaining
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-on expertise in bioimaging, FACS, proteomics/metabolomics, genomics and animal experimentation. The postdoctoral fellow will work in a team with local, national and international collaboration partners
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discovery to identify children at risk for developing kidney disease and to guide personalized treatment strategies. By leveraging advanced technologies in genomics, proteomics, and metabolomics, our goal is
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for this position will join a team of computational biologists to work on multi-omic sequencing datasets (DNA, RNA, epigenetic, spatial transcriptomics and spatial proteomics) in the context of pre-clinical and
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, differentiation, and function. · Utilize gene-editing and transfection approaches where appropriate to develop experimental cellular models. · Conduct imaging, transcriptomic, proteomic, and functional analyses
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. Basic Qualifications A Ph.D. is required. Previous research experience in molecular biology, biochemistry, chemical biology, transcriptomics, proteomics, and/or metabolomics is recommended. Additional
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/Cas9, single cell RNA-seq, cell culture with live cell imaging, immunohistochemistry with confocal microscopy, Ca2+ imaging, coimmunoprecipitation and proteomics. IUSM is committed to being a welcoming
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Qualifications Qualifications: A Ph.D. in neurobiology, developmental biology or cell/molecular biology is required. Experience with methods ranging from RNA sequencing and proteomics to animal behavior is
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, epigenomics, transcriptomics, and proteomics) information. The postdoctoral fellow will develop and refine machine learning methods for analyzing histopathology, clinical, and multi-omics data, collaborate with
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, metabolomics, proteomics) is an asset. Knowledge of data harmonization platforms (e.g., Maelstrom Research guidelines) is an asset. Experience with high-performance computing environments (Unix/HPC clusters) is