22 Statistics "Wellcome Sanger Institute " Postdoctoral positions at Cornell University in United-Kingdom
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working/service dog groups with subsequent statistical and genomic analysis aimed at better understanding behavior traits related to success in working/service dogs and cognitive dysfunction in aging dogs
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field Experience with education research methods, including quantitative research methods and statistics (e.g., proficiency in multilevel statistical modeling using R), and/or experience with qualitative
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acoustic data to evaluate statistical power to detect trends in relative abundance through time, and to inform sampling design. The candidate will be a participant in the Northeast Bat Working Group, NABat
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metabolites. Our group integrates these data with a combination of computational biology, machine learning, and statistical approaches. This position will translate, develop, and deploy genomics pipelines
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, wildlife biology, conservation biology, natural resources, statistics, or a related field, with a focus on quantitative methods in population ecology. Strong mathematical and programming skills, demonstrated
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Postdoctoral Associate: Endangered Bird Conservation in the Western U.S., Cornell Lab of Ornithology
managers (e.g., U.S. Forest Service, U.S. Fish and Wildlife Service, and Bureau of Land Management), and academic researchers specializing in ecology, statistics, and computer science. In addition to working
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Postdoctoral Associate: Endangered Bird Conservation in the Western U.S., Cornell Lab of Ornithology
specializing in ecology, statistics, and computer science. In addition to working with external partners, the postdoctoral associate will be working closely with scientists in the Yang Center and in the Lab’s
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, statistics and computer and data science. The mission of the National Park Service (NPS) is to preserve, protect, and maintain the integrity of park ecosystems for the enjoyment of future generations, and this
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Function We seek a Postdoctoral Associate with experience in statistical modeling who is also interested in natural resource decision-making and species conservation. The successful candidate will use data
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relevant field with a dissertation that included a focus on analyzing high-throughput sequencing datasets. Strong computational and statistical training. Experience with microbiome data analysis including