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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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per year, subject to annual increases. About the Project (Background & Methodology) Autonomous systems such as drone fleets, mobile robots, and sensor networks increasingly use federated learning (FL
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integrated cryogenic temperature sensors. Join our vibrant team in demonstrating cryo-CMOS integrated circuits enabling the next quantum technologies! Job Description Quantum computers and quantum sensors
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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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Contribute to quantum technologies by developing integrated cryogenic temperature sensors. Join our vibrant team in demonstrating cryo-CMOS integrated circuits enabling the next quantum technologies
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Join TU Delft to help shape the future of wireless communication systems. Our research spans 6G, satellite communications, wireless sensing, and non-terrestrial networks (NTN), addressing
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Reference Number BAP-2026-500 Is the Job related to staff position within a Research Infrastructure? No Offer Description Modern embedded AI systems rely on Deep Neural Networks (DNNs) running on resource
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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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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
fitted with sensors, we can also access precise physical measurements. Recent work in AI-for-Science has shown that neural-network-based meta-models can also assimilate measurements. Machine learning