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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
models entails challenges beyond standard decision-making frameworks: calibration, inference, and optimization must operate over high-dimensional, continuous, and structured variable spaces. In
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-ray Magnetic Circular Dichroism (XMCD), X-ray imaging or resonant magnetic scattering. Demonstrated ML experience (e.g., dimensionality reduction, spectral unmixing, Bayesian inference, or physics
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to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more
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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied