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. Until now, specific EN fingerprints of localized corrosion are determined manually. This is a tedious procedure that requires considerable expert knowledge. Artificial intelligence or machine learning (AI
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. Please do not contact us for unsolicited services. Where to apply Website https://www.academictransfer.com/en/jobs/356217/phd-position-machine-learning-m… Requirements Additional Information Website
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of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow based generative
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creation that controls clogging patterns Developing predictive digital rock physics and permeability evolution models from µCT data using machine learning and computational tools (PuMA/CHFEM/MOOSE) validated
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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of an 8-year program on circular battery technology. The project aims to develop new-generation innovative and circular battery packs for heavy-duty trucks, busses, mobile machines, maritime and
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chains. Has demonstrated experience analyzing textual data using NLP or other machine learning techniques. Has excellent English-language academic communication skills (both written and oral) – CEFR level
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variations). As part of the laboratory activities, new challenges are identified: in particular, the use of Machine Learning techniques to predict atomic clock anomalies based on the processing of its
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Sciences at the University of Amsterdam (UvA). BDA works on the development of methodology for data mining, machine learning/deep learning, data fusion, and modelling and application of these methods
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the Netherlands with both scholars focusing on developing and applying state-of-the-art methodologies from the fields of statistics, economics, and machine learning, as well as scholars focusing on consumer