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sustainable food systems. We work to elucidate how system structure mediates sustainability outcomes from management change or policy implementation. Our applied work consists of modeling and field-based
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modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks to minutes
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support for innovative and impactful scholarship. The position includes structured mentorship from Institute faculty, opportunities to lead collaborative projects, contribute as first authors on
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, genetics, genomics, entomology, developmental biology, or a closely related discipline (completed by the start date). Hands-on experience with next-generation sequencing library construction (e.g., RNA-seq
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with next-generation sequencing library construction (e.g., RNA-seq, ATAC-seq, or related). • Demonstrated experience with at least one of the following: ATAC-seq, single-cell or single-nucleus RNA-seq
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approaches to characterize microbial community structure and function, working with graduate students, manuscript preparation and the potential to follow up on observations in research models depending
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health and well-being, cognitive aging and dementia, loneliness and social isolation, and integrative data analysis. Strong analytic skills such as structural equation modeling, multilevel modeling
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interpreting microbiome sequencing and/or metabolomics data, developing novel computational or analytical approaches to characterize microbial community structure and function, working with graduate students
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skills such as structural equation modeling, multilevel modeling, longitudinal data analysis, and/or categorical analysis (e.g., growth mixture modeling) using R, Mplus, and/or SAS. Preferred
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space exploration and life in extreme environments. The Santomartino Lab is committed to supporting the Postdoctoral Associate’s career advancement. The PI will provide structured mentorship, regular