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.\ full-order models, coarse vs.\ fine meshes, sparse sensors vs.\ full fields). The goal is to formalize sources of heterogeneity (input mismatch, output mismatch, partial observability, missing variables
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation
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velocities. To characterise the gas phase at high void fractions, the project will also use a recently developed optical sensor that combines phase detection with Doppler-based velocity measurements
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on a Conventional Imaging System for In Vitro Characterization of Contrast Agents. Sensors 22, 6543. https://doi.org/10.3390/s22176543 Nicolas-Boluda, A., Yang, Z., Guilbert, T., Fouassier, L., Carn, F
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., 2022. Calibrated Photoacoustic Spectrometer Based on a Conventional Imaging System for In Vitro Characterization of Contrast Agents. Sensors 22, 6543. https://doi.org/10.3390/s22176543 Nicolas-Boluda, A
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, particularly in the context of signal estimation through filtering (Figure 1). This problem is particularly relevant for large-scale systems (e.g., energy distribution networks, sensor networks, gene regulation
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
The spectacular development of space systems and sensors, for observing the Earth and other Planets, provides access to numerous geophysical, geochemical and biophysical parameters over vast areas with increasingly
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Allowance** EUR 4736 EUR 710 EUR 660 Context: Agriculture and agronomy generate a wide variety of data (connected equipment, weather, environmental sensors