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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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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural
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to India to help implement the updated model. This would be as needed and no more than two times per year. • Conduct a comparative life cycle assessment of milk produced business-as-usual and after
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modelling tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites. Experience with VIC (or similar hydrologic models), GIS, and large-scale computing
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real-world environments, fine-tuning AI models to classify qualitative data, and building generative AI pipelines to process multimodal data for downstream analysis. Applicants with experience in some
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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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and organization of large data sets. Familiarity with analysis of panel or longitudinal data and working with multilevel models is valued. Additional skills with mixed methods research on related topics
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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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computational methods, proficiency in R or other applicable software packages, ability to develop scripts for R and Echoview, and statistical modeling. Interest in fisheries, fisheries acoustics, aquatic ecology