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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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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
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dynamics in the southwest Cordillera. ● Integrate geophysical and geochemical information (e.g., seismic, thermal, and compositional models) to constrain crustal rheology and structural parameters
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dynamics in the southwest Cordillera. ● Integrate geophysical and geochemical information (e.g., seismic, thermal, and compositional models) to constrain crustal rheology and structural parameters
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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Monitoring (LTVEM) in the hospital for management and diagnosis of epilepsy. The technology is built on brain computer interfaces equipped with a Spiking Neural Network (SNN) and aims at early detection
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and web interfaces for PK/PD model parameter estimation and simulation in popPK/PD, PBPK-PD, and/or QSP approach; model-informed precision dosing and sampling optimization in pharmacometrics approach