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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied to machine learning algorithms in order to get uncertainty estimates for parameters governing
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separation and cosmological parameter estimation, and high-performance computing. This work will also take place within the larger Cosmoglobe framework, and there will be ample opportunities to explore
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collaboration. The successful candidate will be exposed to and trained in both low-level instrumental modeling, high-level component separation and cosmological parameter estimation, and high-performance
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), of the Polytechnic of Leiria Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Undergraduate Positions Application Deadline 6 Mar 2026 - 23:59 (Europe/Lisbon
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the mismodeling of gravitational waves, of astrophysical environments, or of noise artifacts in gravitational-wave inference, The development of Bayesian data analysis techniques to carry out parameter estimation
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Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization (R&D+i) in the fields of Computer Science and Electrical and Computer
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26 Feb 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide array of open problems, both
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Biomechanics Digital Twins for Personalised Medicine”. The central aim of the project is to accelerate the development of digital twins of the heart, primarily by decreasing the time taken for parameter