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developing morphing surfaces enabled by Shape Memory Alloys (SMAs). These adaptive winglets are designed to optimize aerodynamic performance by responding to temperature variations and incorporating active
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discussion, teamwork, and scientific curiosity. We work closely with clinical and industrial partners, ensuring that our research has real-world impact. You will benefit from an international, supportive
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-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning algorithms that maximize the information extracted from
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contribute to the development and implementation of cutting-edge AI solutions for real-time image-guided medical applications. You will work hands-on with clinical data and build robust deep learning
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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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to grow by 20% by 2030, these challenges require a shift from isolated logistics operations to collaborative, connected logistics networks. Upcoming policy measures, including kilometre chargers, CO2 caps
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materials performance. Developing the understanding of the piezoelectric film structures and their functional properties using characterization techniques such as AFM, XRD, SEM and DBLI and detailed analysis