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Field
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. The objective is to develop and validate miniature fibre-optic sensors capable of measuring pressure and temperature in a new generation of ultra-high-pressure rheometers. The intended application is a slit-die
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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
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application process here. About the position Are you motivated to develop next-generation research infrastructure at the intersection of robotics, mechatronics, sensor systems, and life science technology? We
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research infrastructure at the intersection of robotics, mechatronics, sensor systems, and life science technology? We have a vacancy for a PhD Candidate at the Department of Mechanical and Industrial