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electroluminescence and photoluminescence imaging, preferably daylight and field-based methods. Proven skills in data analysis, image processing and machine learning. Experience with PV performance modelling, power
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to the project, uniting experts in battery technology and acoustic signal processing and machine learning. The goal is to harness advanced data science techniques to establish a novel paradigm for online non
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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
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orthopaedic surgery. This role combines medical imaging (ultrasound and MRI), computer-assisted surgical technologies, and the study of how bones and joints move. The targeted starting date is March 1, 2026
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Are you interested in real-time distributed systems, IoT connectivity, and AI-driven automation? The Department of Electrical and Computer Engineering at Aarhus University invites applications for a
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embedded in nanoscopic droplets of superfluid helium. Specific projects include, but are not limited to: 1) Time-resolved imaging of cation-molecule complex formation 2) Time-resolved stereodynamics
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Monitoring (LTVEM) in the hospital for management and diagnosis of epilepsy. The technology is built on brain computer interfaces equipped with a Spiking Neural Network (SNN) and aims at early detection