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Designing and evaluating segmentation algorithms for multi-energy spectral CT data Contributing to or leading work on advanced reconstruction, spectral decomposition, or signal processing methods Integrating
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models to design adaptive, efficient, and intelligent algorithms for hearing assistive devices. Key objectives include improving speech perception in noisy and unpredictable environments, reducing
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will be to develop novel or improve existing AI algorithms and conduct investigations aimed at improving our understanding of the evolution and function of microbiomes. You will be responsible
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. The candidate will design models and algorithms for learning and decision-making under uncertainty, optimized for real-time operation on heterogeneous physical devices. Finally, the position will address how
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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, ethnography, participatory design, and co-design with operators - to capture human, organizational, and socio-technical dynamics. Data-driven and AI-based methods, such as predictive modeling and algorithmic
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the evaluation of converter and drive architectures for edge-resident intelligence; the development of advanced modulation, estimation and control algorithms for high-performance operation; and the integration
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in the inner ear and signal treatment algorithms assist in preparation and testing of the microelectrode arrays at the partner institution collaborate with an interdisciplinary research team in a
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-and-egg" problem of sampling: developing algorithms that learn to bias simulations automatically without requiring prior knowledge of the mechanism. You will contribute to open-source software
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of Geodesy and Earth Observation (GEO). In this position, you will develop algorithms and methods aimed at improving GNSS position integrity and mitigate/reduce both natural and intentional signal interference