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secondary data sources for research; use and analysis of quantitative data in concert with extensive in-depth literature reviews and related written summaries targeting AI topics; completion of human subjects
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of Integrative Data Analysis.” As a postdoctoral associate, you will focus primarily on data analysis and manuscript preparation, with opportunities to publish as first author as well as collaborate on papers with
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sequencing data analysis (shotgun metagenomic, and/or metatranscriptomic), microbial metabolomics, or microbial genetics. Experience designing and conducting experiments that probe the relationship between
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of the experiment, from data analysis to detector operations and HL-LHC detector upgrades. The successful candidate is expected to engage actively in analysis of CMS data and will have considerable freedom in
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of experience achieving impactful results including publications using relevant AI/ML/related techniques and genomic data analysis. Background in and motivation for genomics or/and biodiversity conservation
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community analysis, or microbial metabolism. Demonstrated expertise in one or more of the following: microbiome sequencing data analysis (shotgun metagenomic, and/or metatranscriptomic), microbial
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relevant AI/ML/related techniques and genomic data analysis. Background in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive
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in the biological sciences and experience in molecular genetic techniques, including high throughput sequencing and data analysis. Strong research background with comparative evolutionary questions
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: Record of impactful scientific publications Experience designing and carrying out synchrotron x-ray experiments Proficiency with scientific software for advanced data analysis and/or experimental control
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for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population health To be eligible, candidates must: Have received a PhD in computer