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Field
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and mortality registry, community-embedded settings for participatory research, and cutting-edge methodological expertise in causal inference and artificial intelligence methods for epidemiology and
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the weblike distribution of galaxies in large galaxy redshift surveys, with the corresponding velocity flows inferred from measured galaxy peculiar velocities. These measurements are to be converted into a
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the corresponding velocity flows inferred from measured galaxy peculiar velocities. These measurements are to be converted into a multiscale analysis of the mass distribution, as well as that of the flow field
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Processing/Control Path Planning/Trajectory Planning Multi-Target Tracking/Multi-Object Tracking, Bayesian Filtering, Radom Finite Set filters or closely related multi-target tracking approaches in radar
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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Bayesian inference framework for identifying complex aerospace systems combining with limited experimental data. It can be also used to quantify uncertainties from experimental testing, significantly
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challenging, and new 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
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters