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platform that industrial engineers can use to optimize forming processes. Publish your findings in peer-reviewed journals and present them at international conferences. Collaborate closely with experts
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models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning models combining CT imaging and clinical data, trained on the unique
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leverage assets such as grid-level battery storage, and electrolyzers to have more flexibility when making trading decisions. The challenge then is how to optimally leverage such an asset to make viable
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-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning