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, MASLD, and disease phenotypes (Obesity, Type-2-diabetes) collected in European population studies. You will apply multivariate statistical models and AI-assisted knowledge graphs to guide
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, you employ DNA-based techniques to increase understanding of the determinants of PABs. These include Mendelian Randomization using publicly available GWAS summary statistics to test the causality
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) statistical techniques. Strong interest in how people make decisions and how AI can be used to improve decision-making. Strong technical skills in programming (e.g., Python, R) and mathematics are a plus
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clusters: CASA (Center for Analysis, Scientific Computing, and Applications), DM (Discrete Mathematics), and SPOR (Statistics, Probability, and Operations Research). The domain of computer science is
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Science, Behavioural Science, or Developmental Psychology. You have good research, methodological and statistical skills. You have experience with quantitative research (observational or experimental
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carry out research at the frontier of generative modelling using concepts from statistical physics and neuroscience. For example, we have shown that the phenomenon of symmetry breaking is central to
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) population trajectories and state welfare provision data, available as reports and regional statistics; (meso-level) collective coping strategies through social organisations, collected through their archives
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models available. Project description Nonparametric statistical learning provides a flexible and data-driven approach to choice modeling. Recent advancements have improved its economic interpretability and
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-curative care. Requirements Specific Requirements The successful applicant is expected to have a recent or almost completed MSc degree in a relevant discipline, e.g., psychology, statistics, health sciences
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) population trajectories and state welfare provision data, available as reports and regional statistics; (meso-level) collective coping strategies through social organisations, collected through their archives