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. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms to capture
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, candidates with research interests in areas such as Bayesian methods, survival analysis, experimental design, functional data analysis, clinical trials, precision medicine, and meta-analysis are especially
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experience in AI teaching We understand AI very broadly – and adequate experience would include most topics in modern statistics and topics like Bayesian Machine Learning and Simulation Based Inference (a past
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modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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using MRI scans. DC1 will extend this framework to regional normative models using Bayesian regression and Generalized Additive Model for Location, Scale and Shape (GAMLSS) to derive age- and region
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material
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on the following activities related to Bayesian inference in factorial designs: Construction and elicitation of informed prior distributions; Critical assessment of default prior distributions; Organizing a many
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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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a Bayesian perspective, the use of skew error distributions from well-known skewing mechanisms (eg Azzalini, 1985; Ley 2010), while allowing the parameter(s) controlling the skewness to vary over time
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. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models for long-term forecasting. Collaborate closely with