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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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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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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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with industry partners in climate risk assessment, focusing on: Development of novel approaches to synthetic storm generation Implementation of counterfactual analysis for historical storms Integration
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, focusing on: Development of novel approaches to synthetic storm generation Implementation of counterfactual analysis for historical storms Integration of climate pattern effects (e.g., ENSO) into risk models
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measurements (e.g., release kinetics, seed vigor) – 20% Data analysis, interpretation, and manuscript/report preparation – 15% Coordination of research activities and mentoring of undergraduate assistants – 10
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systems – 50% • Seed coating formulation, treatment evaluation, and analytical measurements (e.g., release kinetics, seed vigor) – 20% • Data analysis, interpretation, and manuscript/report preparation – 15
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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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human-centered design. Applicants with a background in systems approach and expertise in behavior, network, decision, and data sciences are encouraged. Experience in holistic/systems thinking, modeling
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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