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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE STATISTICHE "PAOLO FORTUNATI" | Bologna, Emilia-Romagna | Italy | 2 months ago
? No Offer Description The project is part of GUIDE (Growing Up in Digital Europe), a multi-country longitudinal study on children's development, well-being and life trajectories. It combines Bayesian
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in more recent years, even though criticisms reportedly date back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum
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in more recent years, even though criticisms reportedly date back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum
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to the areas of applied statistics, causal inference, non-parametric and/or categorical data, Bayesian estimation and/or inference, and/or program evaluation is desirable. RESPONSIBILITIES Developing
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based on these models. Performing parameter estimation and uncertainty quantification using Bayesian inference techniques based on experimental and/or synthetic data. Investigating efficient data
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help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis, Bayesian inference, Machine Learning, as well as
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help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis, Bayesian inference, Machine Learning, as well as
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, oscillation, response-time, and evidence-accumulation phenomena. Implement simulation, parameter-estimation, and model-comparison methods in Python, MATLAB , R, or related computational environments
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the areas of applied statistics, causal inference, non-parametric and/or categorical data, Bayesian estimation and/or inference, and/or program evaluation is desirable RESPONSIBILITIES Developing and
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( https://unveil-dn.eu/ ). The goal is to understand how objects are built and age and to support conservation, restoration, and authentication—while training 12 doctoral researchers across engineering and