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Field
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their dynamics to be formulated as systems of linear ordinary differential equations. Bayesian Optimization and Reinforcement Learning methods will be employed to solve the inverse problem of shape and flexibility
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learning or deep learning, preferably with transformer architectures Experience in probabilistic modelling or Bayesian statistics Programming skills in Python, preferably with PyTorch or similar frameworks
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observational data, and the application of advanced methods for longitudinal and prediction modelling. You will also conduct methodological research on Bayesian methods and other innovative methodology
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the “Inverse Problem” component of the project: developing and validating a satellite-based pancake-ice detection algorithm using ICESat-2 wave-damping observations within a Bayesian inversion framework
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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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physics-based insights with data-driven methods—such as physics-informed neural networks, surrogate models and Bayesian optimisation—to explain formation behaviour, identify early indicators of cell
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., Bayesian, hierarchical, time-series), experience with sensor-based data (such as eye tracking, EEG, and heart rate), and proficiency in computational workflows, including distributed and GPU-based systems
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, Bayesian modelling, or other formal models of decision-making and learning). Furthermore, your suitability is further supported by: a track record of publications in peer-reviewed journals; the ability
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statistics, Bayesian statistics, burden mapping, measuring the impact of the environment on disease among others. The PI has projects in both infectious and chronic disease, measuring the impact of
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented