89 machine-learning "https:" "https:" "https:" "https:" "https:" "Bournemouth University" uni jobs 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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. Learning Objectives: The Fellow will learn how wildland fire managers use weather and fuel data to plan and conduct prescribed burns. The Fellow will gain understanding of the range of meteorological data
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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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This research involves conducting fundamental and applied research in the fields of Chemistry, Biology, and/or Chemical Engineering. The fellowship position is based at the United States Military Academy’s Center
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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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well as preliminary research on yield prediction modeling. Learning Objectives: The participant will develop skills in agricultural predictive yield modeling. These will include analysis and interpretation of large UAV
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-property relationships, statistics and probability, applied mathematics, data science, or machine learning. Application Requirements A complete application consists of: Zintellect Profile Educational and
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, the participant will: (1) gain experience in computational modeling to optimize manufacturing high-purity reactive refractory metal powders, (2) learn advanced modeling methods based on density functional theory
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computing facilities at the DOD Supercomputing Research Center. What will I be doing? This project will focus on learning, adapting, and applying US Army Corps of Engineers-developed or supported coastal