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experience in one or more of: large-scale data analysis, time-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department
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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim
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is home to a consortium of postdoctoral fellows who provide modeling expertise for a wide range of projects as integral members of those research teams. Unit URL https://imci.uidaho.edu/ www.uidaho.edu
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Research Engineer/Postdoctoral Position Decision and Bayesian Computation (DBC) – Epiméthée (EPI) Laboratory Institut Pasteur, Paris | 25 rue du Docteur Roux, 75015 Paris Position Overview We
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intelligence, machine learning, big data and network analysis, computational and Bayesian methods, are encouraged to apply. Minimum Qualifications PhD in Statistics or closely related fields with documented
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, to quantum topology, mathematical physics, complex analysis, and dynamical systems. The statistics group research areas include biostatistics, Bayesian methods, environmental and ecological statistics
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equalizer (DFE) and a channel decoder based on PGMs and BP. The proposed research project aims to explore when and how combinedGNNs and PGMs can improve Bayesian receiver design and beamforming for multiuser
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Ability to analyse and visualise disease surveillance and population health data; knowledge of infectious disease transmission dynamics; and competence in applied Bayesian statistical modelling. Strong
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models