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Field
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technologies for transcriptomic, proteomic, and metabolomic studies. Complete the assigned work in time. Complete complex research projects at different stages (advanced through nearly completed). Formulate
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glycolytic rate assays (ECAR/GlycoPER). Function 3 (15%) Analyze, interpret, and integrate transcriptomic, poly(A) mapping, and proteomic datasets using bioinformatic and statistical tools in collaboration
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-cell multi-omics approaches • Analysis of large-scale genomic and/or transcriptomic datasets • Experience with mitochondrial or innate immune/inflammation assays Overtime Status Exempt: Not eligible
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upon the interests and career goals of the individual but will deal with some aspect of fungal and insect molecular biology, fungal genomics/transcriptomics, and/or fungal natural products discovery
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: Mechanistic studies of how m6A alters RNA:protein interactions across the transcriptome Defining the roles of m6A and RNA-binding proteins in brain development, neural function, and neurological disease
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
and/or mouse model systems. Experience with confocal microscopy and live-cell imaging techniques, including FRAP and FRET. Experience with genomics, transcriptomics, proteomics, or other high-throughput
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integrate controlled plant–microbe experiments with metabolomics, transcriptomics, and microbiological analyses to uncover the mechanisms underlying beneficial plant–microbe interactions. The ideal candidate
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approaches for microbiome datasets ability to bridge fields, including microbial ecology, genomics/transcriptomics, statistics, immunology experience or interest in supervising students Location: This position
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publications. Experience working with large-scale biological datasets, including genomic, transcriptomic, proteomic, metabolomic, lipidomic, epigenomic, interactomic, structural, glycomic, or single-cell multi
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fertility using bovine and mouse models. Analyze and integrate genomic, transcriptomic, and epigenomic datasets using computational and statistical approaches. Develop bioinformatic workflows and contribute