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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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20 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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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 days ago
or not in the context of T2D risk. This is of uttermost importance since rare variants, the ones that are present in small groups or individuals, are broadly distributed in the genome, many overlapping
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Materials Required: Further Info: http://www.ece.cornell.edu/ Cornell University School of Electrical and Computer Engineering 229 Phillips Hall Ithaca, NY 14853
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technologies; - Experience with CI/CD methodologies and technologies Minimum requirements: - Knowledge of Software Engineering; - Knowledge of Computer Networks; - Knowledge of Distributed Systems; - Proven
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mass balance simulations that support estimates of snow distribution for biodiversity and ecosystem assessments, as well as hydrological modelling and management plans for ski resorts and hydropower
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at Blindern, Oslo. Job description The PhD fellowship position is located at the Department of Informatics and is hosted jointly by the Network and Distributed Systems Research Group and the Robotics
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20 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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quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution
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-level constraints of distribution networks with DERs, and applications of stochastic programming/approximate dynamic programming approach. Implementation of distribution power-flow methods for DER-rich