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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in
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-time academic or research career. The individual will work primarily on the Duke Predictive Model of Adolescent Mental Health (Duke-PMA) study, a multi-site NIH-funded project that leverages artificial
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candidate will have experience or basic understanding of several of the following areas: high-dimensional data analysis, genome-scale analysis, analysis of genetic data, epidemiology, translational research
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alone ––without a deep understanding of Ecology or Evolutionary Biology would in principle not be enough for this position. Fluency in data analysis in R, and strong experimental skills are essential
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for control and analysis of instruments, applying these systems to the study of human diseases, and acquiring and analyzing clinical data sets. Programming skills should include MATLAB, Labview, Python and/or C
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and immunoprecipitations RT-PCR and RNA analyses Cell transfections and selections RNA-seq and sequencing data analysis RNA modification profiling Lead one or more research projects investigating RNA
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related field prior to the start date. Responsibilities for both positions will include collaborating on the development of research protocols, data collection and analysis, budget and supply management
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; (ii) an impact evaluation of a large-scale tree-growing program in Kenya, Tanzania, Uganda, and India; and (iii) an analysis of financial incentives for smallholder tree growing in Ethiopia. In
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Bioinformatics expertise required for scRNAseq analysis. · Previous cell culture experience. · Perform molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental
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Immunology, Data Science and/or related fields. MD/PhD with molecular biology research experience. Must have experience with analyzing omics data. Familiarity or direct experience with analysis of 10x Genomics