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, ● Methods for heterogeneous treatment effects estimation, ● Methods for multiple exposures, multiple outcomes, ● ML and AI methods for causal inference, ● Bayesian causal inference, ● methods
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to high-dimensional statistics; Bayesian statistics; resampling techniques; digital twins; uncertainty quantification; foundations of machine learning and artificial intelligence; optimization theory and
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via nonlinear parametrizations such as deep networks, dynamical systems and control, Bayesian inference and generative modeling, and randomized linear algebra. Applications of interest are transport
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expression systems and/or liposomes. You take an interest in liquid handling robots, Python and Bayesian optimisation. You are a team player and enjoy working in a multidisciplinary environment. You have a
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-experiments for research purposes, Knowledge of online experiment, task and/or survey platforms (e.g. Gorilla, Prolific, etc.), Awareness of time-series, multilevel, Bayesian, or causal inference analysis
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
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an advantage: Rodent social behaviour, empathy-related behaviour, aggression, fear, or reinforcement learning tasks. Computational modelling, Bayesian statistics, reinforcement learning models, or model-based
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 2 months ago
to have experience in several of the following areas: data processing, statistical analyses, R software, regression models, process-based models such as DSSAT or APSIM, Bayesian statistical analysis
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. Experience with uncertainty quantification, Bayesian inference, inverse modelling, parameter estimation, or model calibration. Experience with high-performance computing, surrogate modelling, reduced-order