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Field
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system models and quantifying uncertainty in their predictions. Conduct fundamental research on the formulation of probabilistic system dynamics models, including knowledge integration, likelihood
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 23 hours ago
. Description: This project will develop a multimodal artificial intelligence framework to characterize and predict dynamic changes in forest structure, aboveground biomass, and carbon storage under hydroclimatic
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analyze spatial and temporal datasets collected from UAS, satellite, ground-based sensors, and other sources. Integrate multi-source datasets and develop predictive models to support crop monitoring and
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, transdiagnostic cohort Integrating theory-driven models with data-driven analytic approaches to improve prediction of symptom trajectories Contributing to study-wide discussions of analytic strategy, model
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: to develop next-generation autonomous crop monitoring and decision-support systems for Controlled Environment Agriculture. By integrating plant sensing, data and crop models, we aim to enable more precise and
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, conducts research at the intersection of theory-based modeling, predictive simulation, artificial intelligence, and plasma control. Group members have backgrounds in plasma physics, applied mathematics
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: to develop next-generation autonomous crop monitoring and decision-support systems for Controlled Environment Agriculture. By integrating plant sensing, data and crop models, we aim to enable more precise and
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, to eventually capture them in physical-chemical models that predict the impact of acidification on marine P cycling. The PHOSFLUX project is a collaboration between the NIOZ (dr. Peter Kraal) and Utrecht
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, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization, energy management, or production scheduling. Good knowledge of integrated energy