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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 28 days ago
fields including health, agriculture and ecology, sustainable development. More information, please visit https://team.inria.fr/scool/projects Odalric-Ambrym Maillard is a permanent researcher at Inria. He
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probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM, data-driven sensor fusion) is a plus. Underwater or field robotics experience
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[map ] Subject Areas: https://careers.epfl.ch/job/Lausanne-Postdoc/1163457655/ Appl Deadline: 2025/11/01 11:59PM (posted 2025/10/09) Position Description: Apply Position Description A postdoc position
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deviation analysis of probabilistic models, and associated problems in PDE, with emphasis on identifying both well- and ill-posed examples and the interplay between probabilistic analysis and the analysis
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built to identify and correct errors, apply bias adjustments, and assess data quality. State-of-the-art multisource blending methods will then be applied (e.g. kriging, probabilistic merging, machine
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, at the undergraduate, advanced and PhD levels. We regularly publish solid contributions at the best machine learning conferences. STIMA is characterized by a modern view of the statistical subject, where probabilistic
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publish solid contributions at the best machine learning conferences. STIMA is characterized by a modern view of the statistical subject, where probabilistic models are combined with computational
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develop risk assessment methodologies for bridges and civil infrastructure, which integrate remote sensing data with physics-based models into a probabilistic decision support system. You will establish a
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of probabilistic modelling, self-supervised learning and representation learning, diffusion/VAE/flow matching/transformer architectures Strong Python, PyTorch/JAX, containerization & MLOps skills; familiarity with
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Optimise and validate: Constrain free parameters using experimental data from muscle calcium imaging and behavioural recordings. Explore motor control: Apply computational approaches (probabilistic