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the attractiveness to the users, we need innovative designs where fixed and flexible services support each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is
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ultrabroadband mid-infrared intrapulse difference frequency generation sources. You will perform multispecies detection in demanding applications such as environmental and exposure monitoring, and in the green
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opportunity to tackle these two complementary perspectives. In the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools
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the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools. The goal is to extract governing equations directly from
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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an interdisciplinary very active consortium called EVOLF. Job requirements Qualified candidates have a Master in physics, chemistry, engineering, or a related field. Successful candidates are motivated by a deep
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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Join us to explore the mechanics of soft matter through a unique blend of theory, hands-on experiments, and machine learning. Job description Soft matter such as polymers and hydrogels
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are motivated by a deep scientific curiosity, have excellent experimental and quantitative skills and possess a drive to learn and to develop new methods and concepts. PLEASE NOTE: The applications will be