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samples using cutting edge technology such as next-generation sequencing to detect and characterize novel and emerging pathogens. The GEIS Branch coordinates whole genome sequencing activities and a
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of the project is to provide a timely update and modifications of this model, as new science and methods have evolved since its development. Learning Objectives: The selected fellow in this project will have the
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, such as: Characterizing geographic differences in infection risk of HPAI in domestic animals. Exploring response options, such as vaccination or surveillance strategies. Learning Objectives: The fellowship
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of economically valuable species and invasive species that may compete with economically valuable species or promote wildfire. Learning Objectives: The postdoctoral fellow will have the opportunity to apply
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an accredited college/university with a research interest in NETL core R&D areas. Additional requirements: Must provide a detailed statement of educational objectives and projected benefits to be realized as a
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identifying insect specimens. Learning Objectives: The selected participant will learn and use forestry field measurement techniques, how to collect tree cores and postprocessing such as dating and measuring
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. Report project findings in scientific articles and management-relevant products. Learning Objectives: The participant will build their experience conducting the full cycle of social science research
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and forecasting wildland fire smoke transport and dispersion. The project objective is to improve both wildfire and prescribed fire operational decision support in various landscapes. They will interact
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development pertaining to chemical and biological detection. You will gain experience with algorithms, data analysis, Deep Learning, Python, pytorch and /or tensorflow, NLP, genetic algorithm, computer vision
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reduction will involve engaging Tribal priorities and knowledges, including use of fire to advance cultural objectives. Specifically, there is a need to develop visual guides and identify metrics