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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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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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biomedical data analysis.Please find more information on LinkedIn:https://www.linkedin.com/feed/update/urn:li:activity:7387170929518379009/
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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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... Your PhD research focuses on several topics like the development of a novel prognostics model based on the evaluation of sensor data and for this specialized methods. Purpose is the updating of digital
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... Your PhD research focuses on several topics like the development of a novel prognostics model based on the evaluation of sensor data and for this specialized methods. Purpose is the updating of digital
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48143 Münster admissions.gspol at uni-muenster.de Please refer to our website for updates and further information: uni.ms/gssp
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), mathematical evolutionary modeling (game theory, dynamical systems, agent-based simulations or other), bespoke probabilistic modeling / (Bayesian) data analysis (e.g., in the Rational Speech Act framework