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models for the fire resistance of LSF walls, including the development of machine learning models, experimental testing, and numerical simulations, within the project “FireLSF – Development of Predictive
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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material damage assessment 3) Developing AI and machine learning models for robot-assisted laser surgery and validate the model by comparing the results to experimental observations. 4) Support the
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models motivated by biological and therapeutic applications are particularly encouraged to apply. Expertise in statistical or machine-learning methods is also welcome, as connection with experimental and
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The position will involve developing new mathematical/computational methods at the intersection of scientific computing and machine learning. At a high level, the project is to build neural network models