128 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Fellowship positions at Zintellect
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scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning
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problem-solving skills Experience developing, testing, and refining machine learning models Excellent written and oral communication skills Experience with publishing in peer-reviewed journals Stipend
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join a community of scientists and researchers in an effort to research modeling approaches related to neural stimulation and inhibition by laser exposure. Research will primarily focus on
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results of your work in peer-reviewed journals. This opportunity will provide exposure and practice with risk management and modeling of invasive pest insects and the training necessary to prepare the
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efficiency and dairy agroecosystem sustainability. Use model calibration, validation, and performance evaluation using USDA-ARS long-term datasets to develop manure nutrient management strategies in the dairy
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Division, Test Science Branch, of the Research and Development Directorate for the Defense Threat Reduction Agency (DTRA) is offering a master's/doctoral level fellowship opportunity in kinetic weapons
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managing diabetes using computer simulation models. Learning Objectives: You will learn: How to synthesize and translate empirical evidence on cost-effectiveness of interventions for the prevention and
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(BDCL), within the Nutritional Biomarkers Branch (NBB), Division of Laboratory Sciences (DLS), National Center for Environmental Health (NCEH), develops and applies analytical methods for measuring
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translation, technical assistance, training and partnership development. For more information, visit: https://www.cdc.gov/nccdphp/dcpc/index.htm https://www.cdc.gov/comprehensive-cancer-control/about/index.html
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for Grain and Animal Health Research in Manhattan, KS. Our mission is to develop economical, effective, and ecologically sound methods for managing insect pests of grain and processed commodities, improve