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, including physics-informed neural networks, neural operators, hybrid physics-ML approaches, and emerging foundation-model paradigms for scientific data. Scientific machine learning is increasingly important
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climate control to direct crop-centric control. This paradigm shift relies on breakthroughs in microclimate sensing, interpreting crop performance by integrating sensor data at different temporal and
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physics of our universe at the nanoscale: from atoms and fundamental particles from a century ago, to the quantum sensors and computers of today, quantum mechanics governs how these microscopic objects and
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Ultrasound sensors for quantitatively measuring
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Ultrasound sensors for quantitatively measuring the viscosity of flows. Job description Continuous, non-invasive measurements of fluid properties are instrumental in factories that produce food
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sensors for measuring the speed of liquids find application in many industrial setups where the dosage of a liquid must be controlled, such as food processing, drug production, microchips and solar panels
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. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming
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monitoring, sensing systems, instrumentation, or transportation infrastructure analytics. Experience working with data-driven technologies such as sensor networks, machine learning, or AI-enabled
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to transform acoustic sensing devices into versatile sensors capable of characterizing the dynamic state of buildings and their inhabitants. By combining multi-microphone acquisition techniques with state