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models and Bayesian approaches to tackle complex, real-world data? Join this PhD project to build dynamic models and study cognitive variability using ecological momentary assessment (EMA). Join us We are
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networks for real-time, adaptive diagnosis. b) Uncertainty in Dynamic Environments: Runtime uncertainties require sophisticated risk modeling; we will employ Bayesian deep learning and deep reinforcement
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optimization-based updates (e.g., stochastic gradient methods and Bayesian learning), Probabilistic performance guarantees, leveraging tools from stochastic systems, RKHS-based learning, and Bayesian inference
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Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions in the T-PRESS Evidence Ecosystem Framework”. The primary objective of the T-PRESS consortium is to
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farms coexist alongside intensive fishing activity and a wide range of maritime uses. The objective is to analyse how the effects of wind farms at the individual level (e.g. fish, marine mammals) and at
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Sustainable Healthcare Decisions. About the project The fellowship period is 3 years and devoted to carrying out a project entitled “Reliable Bayesian prediction models with uncertainty quantification
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | about 2 hours ago
, Ifremer, University of Montpellier, CNRS) and one secondary institution (INRAE). Its research activities are organized around six objectives defined in response to societal challenges related to marine
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manner, in order to achieve the accuracy of high-fidelity simulations while maintaining computational tractability. This is the objective of multi-fidelity modeling. This PhD position is funded through
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
solving complex inverse problems that link measurements to their underlying causes. This PhD interdisciplinary programme focuses on Bayesian methods for estimating physical parameters from high-dimensional
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lattice orientation by EBSD or local chemical composition by EDX [1]. For instance, an original protocol based on Bayesian inference was recently co-developed by LEM3 and ICA to determine the single-crystal