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Field
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sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits
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faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies
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’–mechanical networks built from many sensors and actuators that locally communicate with one another to achieve collective functionality. These active networks could enable next-generation bioinspired robots
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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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our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors
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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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universities and focused instruction by ICFO professors, in a stimulating, international and interdisciplinary environment . PhD-students have the opportunity to take advantage of our network of excellence
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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