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machine learning computer models (i.e. algorithms) for medical imaging, bioinformatics (i.e genomics data including single cell and spatial omics) and drug development applications. Performs analysis
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datasets (transcriptomics, single-cell, proteomics, imaging, etc..), from dataset generation & QC, to the analysis and interpretations of results. Demonstrated expertise critically applying machine learning
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geography and sociology approaches. GET encompasses 7 research teams mobilizing complementary skills in spatial and in situ observation, numerical and analogic modelling, and laboratory experimentation
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders and innovators
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scientific writing skills Preferred qualifications: Hands-on experience with single-cell and spatial transcriptomic analysis Familiarity with multi-omic data integration workflows Cancer biology background
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Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offerEmbedding within a computational team, with extensive experience in computational biology and
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., spatial transcriptomics, single-cell transcriptomics, metagenomics), bioinformatics (including machine learning and artificial intelligence), synthetic biology, organoid technology, CRISPR, molecular
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well amongst actors involved in spatial planning. Limited studies systematically combine methods and insights from these diverse approaches, and an evidence-based spatial and visual methodology
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subject to the terms of the LEO bargaining agreement. The full LEO contract can be found at https://hr.umich.edu/working-u-m/my-employment/academic-human-resources/contracts Job Summary The Program in
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, QGIS, or spatial/exposure analysis in R is a plus. Familiarity with environmental laboratory and field sampling methods preferred. Proficiency with Microsoft Office Suite and other research management