193 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at Zintellect
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different research communities. Learning Objectives: Participants will gain skills in execution of emerging genomic techniques to agrigenomic samples including insects, plants, and microbes on a broad range
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ecosystem services that they provide. Learning Objectives: The participant will learn to utilize ecological simulation models and to design and conduct geospatial analysis of model results to characterize
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are offered an opportunity for an independent research project using lab data to gain experience conducting ecological data analysis, manuscript writing, and publishing in peer-reviewed journals. Learning
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of their research relate to transmission dynamics of VSV and integrated pest management strategies. Learning Objectives: The fellow will have the opportunity to gain experience in entomological and aquatic field
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documenting progress on data processing. Opportunities may also be available to participate in field data collection at various locations in the Pacific Northwest. Learning Objectives: As an educational
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pathogens such as Japanese encephalitis and Rift Valley fever. Learning Objectives: The fellow will learn epidemiological techniques related to modeling parasitic and vector-borne diseases. Opportunities
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diseases such as Japanese encephalitis, Rift Valley fever, and related diseases. Learning Objectives: The fellow will have opportunities to learn field-based techniques related to survey and manage arthropod
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to unravel key indicators of biological relevance during seed quality testing procedures and contribute to a healthy national and international seed trade economy. Learning Objectives: Under guidance of a
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be four (4) years or less. Applicants may be a veteran, or separating veteran, of the United States Armed Services who has received their DD-214 no more than four (4) years prior to the start date
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promoters. Digital Phenotyping: Application of hyperspectral imaging and advanced imaging tools to detect disease traits beyond the visible spectrum. AI-Driven Data Analysis: Leveraging machine learning