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chemoproteomics, chemical biology, and related areas. The interested candidate will work directly with experimental scientists within a wet lab setting to facilitate the management, analysis, and visualization
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Statistics, Mathematics or a related field. Applicants should upload their CV, a cover letter with a brief statement of their background and interests, and contact information only for at least three
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analysis using appropriate machine learning techniques and contribute to the writing of technical papers and research proposals. Duke is an Equal Opportunity Employer committed to providing employment
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to define and lead specific research objectives aligned with the funded aims. Responsibilities will include project management, coordination of data collection and analysis, manuscript preparation, and
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including but not limited to microbial ecology, biochemistry, genomics, biostatistics, molecular biology, microbiology, evolutionary biology. Familiarity with metagenomics data analysis, microbial
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/bioinformatics, and data science. Work Performed · Work in highly collaborative inter-disciplinary environment with clinicians, econometricians, statisticians, and data scientists · Lead statistical analysis
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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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statistical models to investigate gene by environment interactions and to utilize bioinformatics resources and high-dimensional –omics data to elucidate the biological significance of the statistical analysis
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. Engage in a spectrum of research activities including literature review, experimental design and execution, data analysis, manuscript preparation, communications with collaborators and journal editors, and
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, including literature review, experimental design, data analysis, collaboration, and dissemination of findings through conferences and publications. Apply for fellowships and awards, and provide mentorship