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Field
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decisive importance for lifetime performance modelling. The key challenges are the robust integration of a sensor system in the structure and the analysis of measured signals, which are typically strongly
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! This unique research opportunity revolves around the physics of distributed robotic systems, mechanical metamaterials, active matter, and embodied intelligence, combining table-top experiments and
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potential for covering the growing need for high-precision sensors, both for basic science and for industrial applications. State-of-the-art quantum sensing methods rely on spin defects hosted in three
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networks are typically developed for a specific radar configuration and task, and often generalize poorly to other sensors. At the same time, large scale radar datasets with high quality labels remain scarce
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healthcare, communication and sensing, and have the potential to be disruptive to the whole society. A diversity of PIC-based sensors have been proposed, such as environmental sensors (e.g. gas sensing
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detection and free space estimation. However, current neural networks are typically developed for a specific radar configuration and task, and often generalize poorly to other sensors. At the same time, large
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for lifetime performance modelling. The key challenges are the robust integration of a sensor system in the structure and the analysis of measured signals, which are typically strongly affected by environmental
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wide range of markets such as automotive, industrial and aerospace. At our Cottbus site, we develop intelligent sensor systems for demanding applications in industry, mobility, aerospace and beyond
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Nanoswitch sensors
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the Marie Skłodowska-Curie Doctoral Network (ENDOTRAIN). Join Europe’s first doctoral network in digital endocrinology – integrating AI, sensor technology, omics, and clinical medicine to transform diagnosis