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increasingly important, but also more complex, due to rising demands on performance, precision, quality, and sustainability. Bayesian optimization (BO) - a special machine learning approach - represents a
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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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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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
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material
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part of a team Understanding of dynamical systems, time series models, machine learning, Bayesian statistics, experience in handling environmental and climate data is a merit We offer: This position is
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and as part of a team Understanding of dynamical systems, time series models, machine learning, Bayesian statistics, experience in handling environmental and climate data is a merit We offer: This
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. Gaussian Process Regression) model to describe the relationship between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set
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exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 1 month ago
field # Knowledge of dynamical systems and network theory # Previous knowledge of pattern formation theory and of Bayesian inference methods is a plus # Previous programming experience in Python is