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mesocosm experiment with precisely defined nutrient contents in the soil substrates, in which the sensor technology can be tested, as well as the continuous monitoring of the mesocosms with regard to plant
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian ERI@N is establishing capabilities and physical test setups to support
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this impacts forest restoration efforts. You will form an integral part of the Selva lab team led Dr Tommaso Jucker (https://www.selvalab.org ), and will work closely with two postdoctoral researchers and three
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talented and versatile PhD student to develop digital biomarkers from continuous, real-world sensor data. Progressive supranuclear palsy (PSP) is a form of atypical parkinsonism characterized by its highly
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Technologies Initiative (https://wirelesspower.ieee.org/ ). This project is characterized by a strong multidisciplinarity, with applications in the field of IoT. You will work on electronics, wireless
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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | about 2 months ago
electrochemical characterization of enzymatic sensors. Where to apply Website https://pica.cineca.it/unipd/ Requirements Additional Information Eligibility criteria - Italian or foreign candidates who possess, by
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optimization procedures, and bone-quality assessments. Analyze multimodal datasets including radiographs, CT imaging, gait analysis, prosthetic sensor data, and bone-density measurements. Build robust data
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levels. The targeted application will concern multi-sensors based systems for autonomous vehicles embedding AI perception or decision modules. The experiments will rely on embedded platforms available
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-based, wireless communications and autonomy technologies. Collect and archive machine performance data including live video streams, CANBus data to characterize machine performance, times series sensor
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such as protecting embedded systems from vulnerabilities rooted in sensor physics, studying the impact of physical signals (e.g., acoustics, lasers, electromagnetic emissions) on AI and sensing systems, and