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– Advanced Research Training for Additive Manufacturing of the Biomaterials and Tissues of the Future https://cordis.europa.eu/project/id/101226431 . This network has 8 host institutions hiring doctoral
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, and organizational networks, we characterize the dynamics of knowledge creation and application. Current projects include both the production and evolution of scientific knowledge and the application
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intelligence, machine learning, big data and network analysis, computational and Bayesian methods, are encouraged to apply. Minimum Qualifications PhD in Statistics or closely related fields with documented
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” website: https://www.rsm.nl/faculty-research/departments/strategic-management-and-entrepreneurship/phd-in-strategic-management/ Opens external Keywords Entrepreneurship, Innovation, Strategy Renewal
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Bayesian framework and two specific proposed lines of research: (1) constructing suitable priors via neural networks approximations, and (2) enhancing the sensitivity and efficiency of posterior diagnostics
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, including working with multivariate data. Substantial experience in code development and, preferably, experience with Bayesian statistical modelling techniques and software. Willing to develop expert
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, computer science, data science, or related fields. The candidates are expected to have a profound knowledge on the majority of the following topics: Machine learning (deep neural networks) Bayesian machine learning
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foundations in classical probability theory and can be seen as a generalization of the Bayesian framework, bringing an additional degree of flexibility to express different types of uncertainty. In machine
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regression analysis to advanced multilevel models and Bayesian analysis to machine learning, among many others. Our two General Sessions , comprising more than forty classes, are offered in a dual-mode format
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neighborhoods to define using cellular protein expression, then implement appropriate computational approaches to define these neighborhoods (e.g., Latent-Dirichlet Algorithm, network analysis, etc.). Work with