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manufacturing", new AI methods for predicting the outcome of AM printing processes under varying bounding conditions are developed. This involves the design of a cyber-physical system incl. a data management
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systematic uncertainty quantification framework for remote sensing data for bridges. This will be the basis for Bayesian machine learning approachesto predict bridge deformations and manage uncertainty
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use of the structural information for structure-based ligand design projects in order to develop prediction methods to identify new food ingredients and flavor modulators. Key Responsibilities • AI
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and used to predict the development of damage. Based on this, a new maintenance strategy is to be developed that is based on the physical relationships and thus enables better consideration of critical
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prediction technologies, and handheld devices, present novel opportunities for African livestock farmers to adapt to climate change and improve environmental performance. The aim of this research is to