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Field
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work will involve sophisticated bioinformatic analyses, including the application of machine learning techniques, to predict taxonomic, antibiotic resistance profiles and phenotypes from 'omic data. Your
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researchers combining expertise in biochemistry, analytical chemistry, mass spectrometry, and bioinformatics to further develop state-of-the-art proteomics methods that will answer pressing biological questions
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bioinformatics/omics (e.g., scRNA-seq, ATAC-seq) and AI-assisted data analysis in addition to familiarity with mitochondrial assays, live-cell imaging, or high-content/automated analysis Additional Information
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning
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background in evolutionary biology and bioinformatics and interested in leading cross-disciplinary research are encouraged to apply. Successful candidates must hold a Ph.D. Degree In Biology. Significant
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transcriptomics and bioinformatics. Familiarity with microscopy techniques will be beneficial, as will be the ability to troubleshoot experimental challenges. The successful candidate will demonstrate excellent
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with miRNA, including extraction, detection, and inhibition assays, as well as basic bioinformatic analysis of sequencing data -Proficiency in cell culture techniques, including transfection and
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bioinformatics (e.g. RNA-Seq/scRNA-Seq). Main Duties and Responsibilities Perform the following activities in conjunction with and under the guidance of the Principal Investigators (PI): 1. Plan and conduct
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implementing genome-wide association studies of plant-microbiome variation, collecting empirical data, conducting bioinformatic and statistical analyses, manuscript preparation, and mentoring of undergraduate
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implementing genome-wide association studies of plant-microbiome variation, collecting empirical data, conducting bioinformatic and statistical analyses, manuscript preparation, and mentoring of undergraduate