112 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at Zintellect
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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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, 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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-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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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
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animal health, microbiology, and aquaculture engineering. Research Project: The participant will be involved in processes to improve fish health and the efficiency of aquaculture production. Learning
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tools and machine learning for advanced image analysis, weed-crop detection, and mapping. Experience in data collection, processing, and interpretation. Strong background in precision agriculture and
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. Description The Office of Global Research (OGR), at the National Institute of Allergy and Infectious Disease (NIAID), National Institutes of Health (NIH), is seeking candidates who are interested in learning
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animal health, microbiology, and aquaculture engineering. Research Project: The participant will be involved in processes to improve fish health and the efficiency of aquaculture production. Learning
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of laboratory mentors. Activities will include computer programming related to database development, extension of the IDS graphical user interface, and integration of our crop and soil models. Database activities
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spectroradiometers. Ability to apply AI tools and machine learning for advanced image analysis, weed-crop detection, and mapping. Experience in data collection, processing, and interpretation. Strong background in