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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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management. Requisite skills include DNA extractions (ideally from noninvasive sources), PCR, sequencing and basic statistical modeling (e.g., simple regression). Desired skills include qPCR, ddPCR, and/or
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, biology, plant sciences, computer science, statistics or in any related field. Plant molecular biologists with prior experience in molecular genomics and are interested in expanding skillset into machine
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using R for statistical analysis and in statistical modeling. Sound working knowledge of unix shell, high performance compute clusters and git. Willingness to learn and use a scripting language (e.g
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studies. Lead secondary projects applying advanced quantitative statistical analysis to study DNAm signatures, sensitive developmental periods, and subsequent depression risk. Participate in projects using
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to participate in interdisciplinary collaborative projects with other faculty members involved in the grant (statistics/data science, HDFS, psychology), and with other lab collaborators both within and outside