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, spatial statistics, machine learning approaches, large ecological datasets Previous experience with passive acoustic monitoring and/or eBird data Familiarity with ecology and/or ornithology Demonstrated
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, statistics, and ornithology. The postdoctoral associate will be advised by Dr. Laurel Symes ([email protected] ), and will also have the opportunity to work closely with colleagues from other programs
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-to-impact pathway to answer research questions related to weather-related hazards to help communities nationwide. The postdoctoral associate will apply statistical and epidemiological models to examine the
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internationally) Requirements: The successful candidate should have the following qualifications: • PhD in Epidemiology, Data Science, Applied Mathematics, Computer Science, Statistics, Public Health, Economics or
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will contribute to a spatialized, dynamic life cycle assessment of ruminant production systems in the Northeast U.S. using integrated assessment models. The candidate will also contribute
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will contribute to a spatialized, dynamic life cycle assessment of ruminant production systems in the Northeast U.S. using integrated assessment models. The candidate will also contribute
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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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in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations. The research team collaborates
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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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transdisciplinary teams to quantify synergies and tradeoffs between environmental impacts, ecosystem services, and the social and economic dimensions of food systems. Responsibilities Conduct spatially explicit