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Field
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epigenomic, single-cell, and spatial biology approaches to uncover fundamental mechanisms of islet development and disease. Dr. Dhawan’s multidisciplinary, NIH funded program offers the opportunity to lead
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analyzing genomic, transcriptomic, proteomic, spatial multi-omics, imaging, or other high-dimensional biological datasets. · Proficiency in R and/or Python for computational biology and bioinformatics
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, evidenced by peer-reviewed publications. · Strong research experience in computational biology, bioinformatics, or genomics. · Experience analyzing genomic, transcriptomic, proteomic, spatial multi-omics
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on City and Territory, including observation, surveying, documentation, and interpretation of the spatial, social, and material characteristics of territories through direct engagement with places and
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in independent scientific research including molecular and cell biology, histology, flow cytometry and microscopy. Experience with cardiac biology, bioinformatics (scRNAseq, spatial transcriptomics etc
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, Evaluation methods, Mixed methods research, GIS/spatial analysis, Community and/or transportation planning, and Data visualization. Point of Contact Rachel Eligibility Requirements Citizenship: U.S. Citizen
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troubleshooting. · Lead genomic analysis and integration of multi-omics data including microbiome and cell stress phenotypes. · Lead collaboration with spatial transcriptomics and functional genomics
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analysis and integration of multi-omics data including microbiome and cell stress phenotypes. · Lead collaboration with spatial transcriptomics and functional genomics team (external). Assist with
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with spatial resolutions approaching tens of nanometers. However, current reconstructions are slow, expert-driven, and difficult to scale, preventing real-time experimental decision-making and broader
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deployed inside an XR space. This agent will serve a dual development goal: functioning as an interactive, simulated guide that outlines the features of the UTOPIA Lab and acting as a spatial manipulation