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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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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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of variable distributions [13,14]. Graphic neural networks (GNNs) are new inference methods developed in recent years and are attracting increasing attention due to their efficiency and ability in solving
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the requisite experience. A2 Knowledge of mathematical and statistical methodologies including several of: Statistical modelling and inference, Bayesian statistics and probabilistic modelling, Inverse problems
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polycrystalline material during plastic deformation in order to eventually predict the manner in which materials deform and fail. As a first step, we wish to infer a distribution of the directions of deformation
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programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
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. The postholder will be based in the Center for Communicable Disease Dynamics within the Department of Epidemiology, and will be a member of the HIV Inference Group a geographically distributed and substantively
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, etc. *Knowledge of Bayesian inference and sensor fusion. *Demonstrated ability to write peer-reviewed scientific manuscripts. *Knowledge in Dockerisation, Kubernetes, Django and Geoserver. *Some
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in mechatronic hardware and software You have a solid foundation in probability and statistics for Bayesian modelling, uncertainty quantification, and causal inference You have a team player mindset, a
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and Bayesian inference frameworks. The vacancy is for a full-time post available from 1st April 2026 with a contract of 36 months. What you will get in return: Fantastic market leading Pension scheme