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Field
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motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in constrained environments - Data-driven and learning based control - Meta-learning for emergent behavior in
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very low; Propose characterisation of the soil properties collected from different studied farms; Test how to Improve soil organic carbon content using organo-mineral resources under controlled condition
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farms; Test how to Improve soil organic carbon content using organo-mineral resources under controlled condition; Assess the effect of using organo-mineral resources on soil carbon stock in the field
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process. The second AI algorithm will take these PADs, alongside various solar eruption data, to predict the energy spectra of SEP events as measured by spacecraft. These predictions will be directly
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, Agronomy, modeling, biostatistics, or related field The applicant should have documented knowledges in Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming
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that control the response to low oxygen conditions in Marchantia polymorpha. They will contribute both to the practical work with plants but also some bioinformatics work on protein structure and function
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
of excellence for outbreak analytics and disease modeling, named Insight Net. This position’s efforts will focus on developing predictive and analytic models of infectious disease and will use dynamic models and
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conducting lifetime modeling, developing advanced condition monitoring techniques, and applying data-driven analytics for lifetime prediction. You will play a central role in integrating experimental insights
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production and quality control will help save natural resources as well as reduce waste material and energy consumption. Formulation and test methods using mathematical modelling and prediction tools. Fouling
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run