199 machine-learning "https:" "https:" "https:" "https:" "https:" "The Francis Crick Institute" positions at Zintellect
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and Data Science (including machine learning and AI for defense applications) - Systems Engineering and Engineering Management - Industrial Engineering and Production Management - Mathematical Modeling
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machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of
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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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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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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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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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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