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modelling, geospatial 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
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Gravitational-Wave Astronomy Using Artificial Intelligence, to work on computational Bayesian inference methods and their astrophysical applications. Southampton's School of Mathematical Sciences is home to a
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Gravitational-Wave Astronomy Using Artificial Intelligence, to work on computational Bayesian inference methods and their astrophysical applications. Southampton's School of Mathematical Sciences is home to a
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of the following topics will be appreciated, but mostly we look for smart people who enjoy learning new things: Approximate Bayesian inference Differential geometry Numerical computations (ideally with experience in
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of interacting particle methods for Bayesian inversion by including model error in the likelihood evaluation. As model problem, we will consider the inference of parameters in phenomenological models for cardiac
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through to large-scale individual-based simulation as well as statistics and Bayesian inference. This highly motivated, collaborative research group leads funded, international consortia in modelling, NTDs
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and BAT.jl projects. The position also offers opportunities to contribute to research in Bayesian inference and its application to physics in general. The DEMOS project aims to develop state-of-the-art
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 14 hours ago
models entails challenges beyond standard decision-making frameworks: calibration, inference, and optimization must operate over high-dimensional, continuous, and structured variable spaces. In
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development and statistical modelling in resilience assessment (e.g., dynamic/latent-variable models, Bayesian hierarchical models, causal inference, time-series analysis, cognitive modelling) Build robust
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include, but not limited to, computational approaches such as AI and machine learning; methodological foundations and computational approaches for AI for biomedicine, Bayesian inference, cancer imaging