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multimodal fusion, robust pose estimation, and real-time processing. Together, these roles form a cohesive effort to bridge algorithmic innovation with practical applications in next-generation media
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advanced algorithms that efficiently utilize UWB signal features (RSSI, channel impulse response, phase and amplitude data, Doppler maps,..) to support both high-precision localization and radar-based
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development of (open source) tools and algorithms for numerical simulations; o supervise PhD students conducting research in the field of this vacancy; o take responsibility for project coordination
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networks, etc. In this PhD position, you will build on our expertise in reinforcement learning for flexibility exploitation, and design of AI-based energy management algorithms to coordinate individual and
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fluid-structure interaction (FSI); - Development of techniques for deforming fluid domains, including Chimera techniques. The doctoral research needs to realize algorithmic improvements in the topics
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medicine. This vacancy focuses on the algorithmic aspects of these techniques. We are seeking to recruit a strong researcher with a background in computer science. The ideal candidate can provide computer
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extension to four years, will focus on leveraging the next generation of evolutionary algorithms to evolve efficient, robust, and interpretable predictors and data processing algorithms. A crucial aspect will
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theoretical background for MIMO related research, and have attended courses such as Information Theory, Signal and Systems, Modulation and Detection. Experience with OFDM or single carrier baseband algorithms
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the field of analytical and/or simulation methods for composite materials. You have extensive experience with development and implementation of algorithms for modelling of composites You have experience with
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, exploring multimodal fusion, robust pose estimation, and real-time processing. Together, these roles form a cohesive effort to bridge algorithmic innovation with practical applications in next-generation