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situations dynamiquement, nous couplerons 1) une approche numérique associant modèles graphiques probabilistes et théorie des fonctions de croyances pour sélectionner les objectifs scénaristiques adaptés au
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analysis / computer vision, ideally on microscopy or time-lapse data Experience in at least one of: tracking / time-series analysis, probabilistic modelling / uncertainty, real-time or streaming pipelines
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of Mathematical Sciences, University of Delaware The Mathematical Sciences Department (https://mathsci.udel.edu ) at the University of Delaware seeks to appoint two tenure-track assistant professors in the area of
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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join the Tang Lab. The Tang Lab (https://tangxinlab.org/ ) develops explainable, autonomous, and multimodal artificial intelligence (AI) systems to advance biological discovery. Our research integrates
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of novel mechanistic insights is gained through the application of novel probabilistic deep-learning models that automatically extract biological and statistical knowledge from your in vivo perturbational
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safer, more reliable, and more sustainable renewable energy systems. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods
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calculus, type systems, and models for probabilistic programming languages. Permanent members : A. Saurin, T. Ehrhard, C. Faggian, P.-A. Melliès, D. Kesner, G. Bernardi. Where to apply Website https
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engineers and scientists, you will use these models for scalable vision tasks, instance segmentation, tracking, classification, and more. You will utilize probabilistic models to produce uncertainty-aware