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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems used in power electronics and energy infrastructure. The research will investigate how machine learning
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recycling of components, enabling a more circular life cycle. The work will contribute to a new paradigm in the development of power electronics that incorporate disassembly, reuse, and remanufacturing
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studies in healthcare environments, such as observations and interviews, with prototype design and development. The project will develop new knowledge on how robots in clinical settings can communicate
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of creative professionals, in particular architects, in integrating decision support during design ideation. Your work will combine requirements gathering with interactive system development and empirical
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through online surveys and interviews, prototype development for accessible setup and operation of nanoservers (both on web and mobile platforms), and longitudinal evaluation of the prototypes through live
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, and developing systems capable of identifying and prioritizing the user’s intended sound sources. Overall, the PhD works contribute to the development of intelligent, user-aware hearing assistance
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applications for a PhD position within the project “HVDC Subsea Electrode Unit”, starting from May 2026 or soon hereafter. The 3-year employment is funded by the Energy Technology Development and Demonstration
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research meetings, presentations, and constructive feedback are part of our regular work. The PhD student will join a team of close colleagues eager to support your academic development and help integrate