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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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. Integrate the feed chemistry data being developed in a parallel project. Travel to India to help implement the updated model. This would be as needed and no more than two times per year. Conduct a comparative
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. Applicants must have experience in the handling and organization of large data sets. Familiarity with analysis of panel or longitudinal data and working with multilevel models is valued. Additional skills with
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or willingness to develop skills in analytical techniques such as GC–MS or related methods for quantifying seed-applied compounds Experience with statistical modeling, experimental design, and multivariate
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communities using model and non-model organisms. The individual is required to use tools in chemical ecology, genomics, molecular biology, and AI-driven predictive modeling in the research project. Specific
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-insect community as a model for hypothesis testing in molecular evolution. The individual will use methods such as RNA-seq to identify genes and regulatory sequences that drive plant toxin detoxification
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: Leading system mapping for multiple zoonotic systems, including Hendra virus in Australia and Nipah virus in Bangladesh Helping organize, and participate in, Participatory Model Building with local
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quantitative ecology, applied statistics, or a related field with strong background in statistics and model development. Experience with R and analyzing spatial datasets. Ability to apply quantitative methods
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-based model for implementing similar changes more broadly. The position target start date is no later than June 1, 2026 with preference for a candidate who can start in Fall 2025 or Spring 2026
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quantitative ecology, applied statistics, or a related field with strong background in statistics and model development. Experience with R and analyzing spatial datasets. Ability to apply quantitative methods