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by combining all available data, taking advantage of the varying temporal resolution and different time spans that the records cover. This work will involve Bayesian tools developed by our research
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for estimating soil organic matter dynamics. Demonstrated experience in applying Bayesian statistical approaches to soil science questions. Knowledge in soils and soil management issues of Ohio and the greater
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: • Strong background in modelling, including spatial and temporal/dynamic modelling, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams • Experience with data
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. To that aim, both Stein-based bilevel optimization, empirical Bayesian and unsupervised deep learning approaches will be considered. The recruited postdoc researcher will tackle both implementation challenges
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statistical methods such as dimensionality reduction and Bayesian modeling. This project offers access to a rich, curated clinical dataset and collaboration with leading neurologists, neurosurgeons, and data
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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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, particularly radionuclides, on a continental scale. The aim is to develop a new class of inverse Bayesian models, STE-EU-SCALE, combining innovative forward dispersion models, machine learning techniques, and
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, Statistics, or related fields No experience required Skills: Strong expertise in the theory and application of birth-death and related stochastic processes Proficiency in both frequentist and Bayesian
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of metabolic and cellular properties Phylogenomic analyses of obtained MAGs, including extraction and evaluation of marker genes, performing ML and Bayesian analyses of (concatenated) marker gene sets using
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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