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parameters by trial-and-error, leading to a time consuming sub-optimal selection. In the domain of high precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities
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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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deep learning models, testing and optimizing the models documenting all performed tasks in detail, visualizing the model results, and writing technical reports investigating related software and
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offshore wind OEM—invites applications for a fully funded PhD position on the “Development and Implementation of an Autonomous Decision Support System for Optimized Maintenance in Wind Turbine Infrastructure
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, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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optimization, and technology development as part of ongoing projects focused on advancing Power-to-X solutions for a sustainable energy future. Expected start date and duration of employment This is a one–year