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. The work will apply state-of-the-art three-dimensional atmospheric chemistry and circulation models, together with advanced statistical techniques (optimal Bayesian, Markov Chain-MonteCarlo, etc.) to solve
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, so that it can be easily used in practice (fast optimization, embedded decision-making, online updating). 1. Design a lightweight statistical/probabilistic surrogate model, integrating: • an estimation
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
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associated with phenotypic (biomechanical and metabolomics) traits. Estimate locus-specific effect sizes and quantifying genetically-driven phenotypic variations. Develop Bayesian models and/or deep learning
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in modern scientific computing -Excellent communication and collaboration skills Preferred -Experience with simulation-based inference and Bayesian methods -Familiarity with cosmological simulations
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individual rates of ageing. Role You will extend BrainAGE from global estimates to regional normative models using Bayesian regression and GAMLSS to derive age- and region-specific reference distributions
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mathematical information science approaches, such as scientific machine learning. Potential research topics include, but are not limited to: (1) Bayesian estimation of 3D velocity structure models using ocean
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experimental methods. Develop and apply methods for demultiplexing, normalization/QC, effect-size estimation, biological inference, and predictive modeling. Contribute to biological manuscripts and methods
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to implement advanced computational pipelines, including machine learning, deep learning, Bayesian inference, and probabilistic mixed membership modeling for innovative research. · Contribute
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buildings closed days for all full time staff (Part time workers should pro rata this by their FTE). Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the