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tower (eddy covariance) data as demonstrated by publication in top peer-reviewed journals. Strong data-driven and process-based modeling and data analysis skills and proficiency with JMP, ArcGIS, and
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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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cellulose-based recyclable food packaging for cheese and fresh produce preservation, focusing on the development of base papers, films, and barrier coatings, using nanocellulose materials and other bio
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design, modeling, mapping, coastal planning and management, or related activities. Demonstrated understanding of interactions between the built environment, coastal processes, and natural environments
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to offer. Qualifications: Required: PhD in ecology by start date Experience in plant phenology, biogeography, and spatial and temporal modeling (Bayesian and frequentist) Expertise in R or Python, GIS, big
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-doctoral researcher with a strong quantitative background in biology, evolution, or social science, and previous experience in mathematical modeling or behavioral experimentation. Purpose: Complete a multi