Quantum Machine Learning
Funds research building and benchmarking quantum-enhanced machine-learning methods for real-world, data-heavy problems.
EuroHPC Joint Undertaking runs this as a single-stage Research and Innovation Action, expecting to fund two consortia from a EUR 6,000,000 pot, each receiving between EUR 2,000,000 and EUR 3,000,000 at an EU funding rate of up to 50% of eligible costs — a lower rate than the Horizon Europe default. Expected project duration is 48 months, with work expected to start around TRL 3 to 4 and reach TRL …
This topic funds research and demonstration of Quantum Machine Learning (QML) methods, including quantum supervised learning, quantum convolutional neural networks, quantum-native models, quantum reinforcement learning and quantum unsupervised learning, that show measurable gains over classical baselines. It wants proof-of-concept demonstrators in domains such as climate modelling, Earth observation, healthcare, materials discovery, finance, robotics, manufacturing or cybersecurity.
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