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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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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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to improve R&D efficiency, and the influence of investors and other external actors on entrepreneurial outcomes. Our research also examines decision-making under uncertainty, including the use of Bayesian
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implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
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the Netherlands’ national bird, the black-tailed godwit. Join our team! We seek a quantitative, ecology-minded PhD candidate to expand our state-of-the-art Bayesian Integrated Population Model (IPM
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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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close to the nest [1 ] but to better understand foraging, we need landscape level detail. The direction of the project can be tailored, but could include developing and applying Bayesian ML approaches
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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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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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. 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