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Field
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: Experience with surrogacy analyses using regression model and/or meta-analytic model including Bayesian methods and knowledge of continuous glucose monitoring data (or any digitally derived endpoint data
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—or a strong affinity with—Bayesian Statistics, who is eager to contribute to our overarching research programme in high-dimensional statistics. As Associate Professor, you will play a leading role in
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incorporate methods that integrate: - Mendelian randomization and genetic instruments - Bayesian hierarchical models and Gaussian graphical models - Multi-layer data integration across tissues and omics
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approaches to data analysis. We welcome applicants working across a variety of approaches, particularly computational and Bayesian, and with a range of data, including text, survey, and panel data. In
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to develop the statistical inference side of the project, including likelihood-free and Bayesian approaches for fitting stochastic simulators to high-dimensional single-cell data. The successful applicant will
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recognized research centers and institutes. The incumbent will join a collaborative department with internationally recognized expertise in biostatistics, statistical omics, bioinformatics, Bayesian
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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cancer cohorts. • Proven ability to develop novel computational and AI-driven methodologies, including Bayesian generative models, phylogenetic inference tools, and algorithms for multimodal data
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articles in topics related to the project objetives (maximum 4 points). 4. Personal interview if deemed necessary (maximum 1 point). Additional comments In compliance with Section 8 of the Resolution
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handling methods (e.g., FIML, multiple imputation) suited to longitudinal attrition. (EF) Apply advanced hierarchical/multilevel models using both frequentist (lme4, glmmTMB) and Bayesian (Stan, brms, rstan