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previously acquired knowledge. We will study collaborative learning scenarios, where multiple devices or sensors jointly process and learn from data streams. Such settings introduce additional challenges
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, signal processing, and electromagnetic sensing and countermeasure technologies, with a focus on Counter-Unmanned Aircraft System (C-UAS) applications. The successful candidate will contribute to advancing
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Engineering, Electrical Engineering or related fields, with a solid academic record excellent programming skills experience in wireless communication, embedded systems, hardware design, signal processing
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, wearable sensor data, and behavioral measures. · Collect, process, and analyze multimodal datasets, including neural, physiological, and motion-tracking signals. · Develop and refine research protocols and
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multiple processes may be involved, coexisting or even compounding one another. All proposed mechanisms implicate the sensory hair cells of the cochlea. Outer hair cells (OHCs) amplify mechanical vibrations
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multiple seminars, workshops and conferences, a curated exhibition, a database, and the development of a project website. Research Focus This PhD position explores the use of digital humanities
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PhD fellowship 2 – Alexander von Humboldt and French-German Networks in the Early History of Ecology
relevance for environmental studies and scientific discourse Project activities include multiple seminars, workshops and conferences, a curated exhibition, a database, and the development of a project website
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the PhD Student will be positioned to the section for “Applied Power Electronic Systems”. Your work tasks Asynchronous grids (a-grids) decouple synchronous power systems into multiple compartments with
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platforms for selected range of analytes, which can be adaptable to multiple sectors. These platforms will enable rapid in-field testing and point-of-care diagnostics, eliminating the need for complex fluid
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dynamics are further shaped by interactions among multiple GFM units and the surrounding grid strength. Conventional small-signal models are therefore inadequate, motivating large-signal modelling and