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entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools
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Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/ ). The candidate will enrol for a PhD in Chemical Engineering at the University
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied
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radio interferometry data, particularly very long baseline interferometry. Experience with or skills relevant to statistical modelling and Bayesian inference. Demonstrated familiarity with the fields of X
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like LiteBIRD and FOSSIL. We have a large international network of collaborators, and as a doctoral fellow you will have many opportunities to travel and collaborate with researchers at other