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can be used as a practical tool to identify and adjust recipes that, for a given machine and processing window, fulfil defined target criteria. Building on existing evidence that Machine Learning can
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our research portal . Opportunistic screening envisions a scenario in which all acquired medical images are studied in minute detail to detect the early signs of any disease. When combined with AI tools
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of any disease. When combined with AI tools, this has the potential to detect diseases earlier, giving the best chance of improving patient outcomes reduce the burden placed on radiologists and democratize
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dissemination is expected to focus on leading Human-Computer Interaction venues. For further information about the project, see: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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adaptation to changes such as route closures, infrastructure modifications and new mobility technologies; Translating model insights into tools and knowledge relevant for urban planning and transport system
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At the Faculty of Medicine, Department of Health Science and Technology, one or more PhD stipends in Human-Machine Interaction are available for appointment from October 1, 2026, or as soon as
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reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration, experimental testing, or hardware-in-the-loop
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of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration