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priority in the regional aircraft sector. A fundamental enabler for this transformation is the availability of airworthy, high-performance Battery Energy Storage Systems (BESS), capable of meeting the
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of HBGI interventions at three European sites; · Monitoring of physical, ecological, and social performance compared to traditional grey infrastructure; · Iterative design optimization in
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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
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-performance Battery Energy Storage Systems (BESS), capable of meeting the stringent energy, safety, and integration requirements of aviation. The main objective of the postdoctoral position is to develop a high
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initiatives and data-driven reaction optimization. This is what you are going to do This research offers a unique opportunity for highly multidisciplinary exploration within a diverse and collaborative team
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issues. Thus, there is a growing demand for efficient and reliable digital CIM-based neuromorphic system design which includes techniques such as reliability-aware mapping and optimization techniques as
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, there is a growing demand for efficient and reliable memristor CIM-based neuromorphic system design which includes techniques such as reliability-aware mapping and optimization techniques as well as high
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performance on an innovative VTOL platform (https://aerogriduav.com/ ). AI models to predict ship motion to optimize landing timing. You will work at the MAVLab, which is part of the Control & Simulation
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two one-year postdoctoral positions available, centered on our RoboChem initiatives and data-driven reaction optimization. This is what you are going to do This research offers a unique opportunity for
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includes techniques such as reliability-aware mapping and optimization techniques as well as high-quality, and cost-effective mitigation schemes that can guarantee efficient and reliable operation. The