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identified in other WPs. The model construction will be informed by qualitative and quantitative knowledge of supply chain processes through dialogue with stakeholders, and model parameters will be estimated
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of methodologies to detect and locate seismic events recorded in DAS data Development and use of tools to estimate source parameters and fault mechanisms from DAS data Integrate and compare detection thresholds
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, yarns and textiles, and their associated processes. The duties for the Post-Doctoral Research Fellow include research on how modifications of manufacturing parameters impact textile performance, how
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TPMS data, high-speed wheel encoders, CAN data, accelerometer data, and acoustics data. In addition to other cloud-based data for weather-friction estimates and crowdsourced vehicle data for estimating
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negotiable, preferably in autumn 2025 or in 2026. Background Northern wetlands emit large amounts of methane (CH4), a potent greenhouse gas. There are high uncertainties in the estimation of wetland CH4
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general predictive modeling methods, including model design, parameter estimation, sensitivity analysis, and model evaluation. An understanding of data acquisition and curation methods for real-world data
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general predictive modeling methods, including model design, parameter estimation, sensitivity analysis, and model evaluation. An understanding of data acquisition and curation methods for real-world data
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in the southwest Cordillera. * Integrate geophysical and geochemical information (e.g., seismic, thermal, and compositional models) to constrain crustal rheology and structural parameters within
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assessing the effects of Low Earth Orbiting satellites on LSST data and resulting systematic errors in dark matter and dark energy posterior cosmological parameter estimates. Skills must include database
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infrastructure monitoring, as well as connected autonomous vehicles Integrating multi-modal sensor data with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation