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national scale programmatic decisions and policy. Specific activities include: Operationalize, and where needed, improve Bayesian spatio-temporal feral swine abundance model allowing predictions to be
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inference (otherwise known as spectral retrieval), which involves using forward models in conjuction with Bayesian or machine learning-based techniques in order to derive posteriors on parameters of interest
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interconnected research tracks: Post-Fire Hydrology and Debris Flow Hazard: Fellows will collaborate with researchers to collect and analyze field data related to post-fire runoff and sediment transport
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responses to environmental disturbances. Fellows will practice a variety of data collection, monitoring, and analysis techniques by collaborating on the following research track: Post-Fire Hydrology and
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insecticides which are highly toxic to beneficial insect populations. Specific objectives include: Establish a seasonal crop, non-crop, and winter cover crop host monitoring program; Evaluate overwintering
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mycobateria and brucella families in various species of animals using serological tests as part of the eradication program. Learning Objectives: The participant will have the opportunity to learn about zoonotic
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management methods. The fellow will be a part of guided experimental design, data analysis, and manuscript preparation. Learning Objectives: To support the research and training of the postdoctoral research
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of MPS-based potency assays in assessing antibody products. Learning Objectives: If selected, you will learn how to: Handle pathogens safely, adhering to all the laboratory and personnel safety rules and
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data and provide experience using the SHAPE tool to report soil health results back to participating farmers. Learning Objectives: Under the guidance of a mentor, the fellow will gain hands-on experience
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reporting soil health results back to participating farmers. Learning Objectives: Under the guidance of a mentor, the fellow will gain hands-on experience with laboratory methods for soil health assessment