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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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infectious disease epidemiology and mathematical modelling in Biology and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good
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expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
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and/or Python. Experience in, and aptitude for, complex statistical modelling (inc. mixed effects regression models and/or Bayesian statistics). Excellent written and spoken English. Desirable (traits
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main project by addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods
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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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agents Jonathan Doucette Doctor of Philosophy in Physics (PhD) Probing Brain Tissue Microstructure with Magnetic Resonance Imaging through Bayesian Learning of Signal Dynamics Evelyn Arriagada Doctor
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will be developed using the OpenFOAM toolkit. A modelling workflow will be created, and then used as the basis for the optimisation, potentially using tools such as Bayesian Optimisation. In addition
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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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the overall structure of the cosmic web are the various versions of the scale-space MMF/Nexus pipeline and the stochastic Bayesian Bisous method. To improve, extend and deepen the analysis to a full dynamical