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turbine blades. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms
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, including sequential Monte Carlo methods, Gaussian processes and Bayesian compressed sensing. Applicants from different backgrounds are encouraged to apply depending on the specific nature of the project
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find some of our publications here: https://i.giwebb.com/research/computational-biology/ Required knowledge A solid grounding in artificial intelligence and machine learning. Learn more about minimum
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complemented with a supersonic module grounded on the work of Bufi & Cinnella (link to the research paper). In a second step, using Bayesian processes (Lam et al., 2015) and new acquisition functions
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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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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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robability Theory, Stochastic Analysis, Mathematical Statistics, Bayesian Statistics are encouraged to apply. Responsibilities for these positions include mathematical research, undergraduate and graduate
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of the experimental approach will include: Bayesian reconstruction of events on billion-year timescales, determination of optimal embeddings and encodings for protein structures, multiple structural alignments
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expertise/interest in Bayesian methods for addressing measurement error. Ideally PhD within the last 5 years. Advanced level experience with R, desired knowledge of Nimble, Overleaf. Excellent communication
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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