Quantum Machine Learning

This call aims to strengthen Europe’s scientific and technological capabilities  and advance research at the intersection of quantum computing and artificial intelligence.

Status: OPEN

Reference: HORIZON-JU-EUROHPC-2026-QML-07

Publication date: 2 June 2026

Opening date:

Deadline model: Single-stage

Deadline date: 28 January 2027, 17:00 (CET)

Description

With the objective of advancing and unlocking new capabilities for data processing, optimisation, and modelling, the expected outcomes  of this call are meant to:

  • Use hybrid approaches by combining quantum processors with classical HPC systems which can address computational bottlenecks while maintaining scalability and robustness , are expected to
  • Contribute to development, validation, and demonstration of Quantum Machine Learning (QML) methods, including novel quantum, quantum-inspired, or hybrid algorithms, performance benchmarking, and noise-aware strategies.

Particular emphasis is placed on scalable solutions capable of handling large and complex datasets, as well as on the development of quantum-native learning models that can demonstrate clear advantages over classical approaches.

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