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to details. You care about having a positive impact with your research. are excellent at quantitative reasoning. You have a rigorous statistics training in causal inference, and a strong command of Stata. You
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of the Department of Mathematics at Radboud University (Nijmegen, Netherlands), and join the research group of Laura Scarabosio, funded by the NWO Vidi programme ’Taming Frequency in Bayesian Inverse
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different approaches, the most prevalent is polygraph testing which infers deception through the measurement and analysis of physiological responses (e.g., blood pressure, electrodermal activity). However
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and inference with cluster-dependence, high-dimensional parameters, or outliers. Other possibilities could be, for example, theory of bootstrap or nonparametric inference. For more information and
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of Sciences. You will be part of an exciting research project aimed at understanding rapid evolution and adaptation in butterflies flying at high elevations. The goal of the PhD work is to infer climatic niche
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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with experience in causal inference using panel data (e.g., Difference-in-differences) solid knowledge of Stata, R and/or Python for conducting econometric analysis previous knowledge of conducting
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strategy, a probabilistic (e.g. Gaussian Process Regression) model to describe the relationship between process parameters and material properties will be developed and subsequently exposed to Bayesian
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Matias, Adrián Villaseñor, Rowena Jacobs Topic 4-Machine Learning for Causal Inference in Health Policy Assessment for Decision Making Supervisors - Dr Julia Hatamyar and Professor Andrea Manca Topic 5
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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