QuantERA Call 2025 Partner Search Tool


This is a match-making section for QuantERA Call 2025.

General Information

  • Type: Partner looking for project
  • Organisation: August-Wilhelm Scheer Institut gGmbH
  • Country: Germany (DE)

Research area

  • Call topics:
    • Applied Quantum Science
  • Keywords:

    Quantum Machine Learning Optimization Hybrid Quantum-AI Quantum Computation

  • Brief description of your expertise / expertise you are looking for:

    The August-Wilhelm Scheer Institute (AWSi) is an applied research institute focusing on the intersection of artificial intelligence, quantum computing, and digital innovation. Our interest lies in developing and applying advanced methods in Quantum Machine Learning (QML), Quantum Optimization, and Hybrid Quantum-AI architectures that bridge classical and quantum systems for enhanced computational performance and intelligent decision-making. We combine deep expertise in AI model design, optimization algorithms, and data-driven process innovation with a strong focus on practical applications in industry and science. Our research aims to exploit quantum advantages for solving complex optimization and learning problems, supporting use cases in manufacturing, logistics, energy systems, and digital ecosystems.

  • Brief description of your project / the project you would like to join:

    We are interested in joining a project that explores the integration of Quantum Machine Learning, Hybrid Quantum-AI architectures, and advanced optimization techniques to address complex real-world challenges in production, energy, or logistics systems. The project should aim to leverage quantum-enhanced algorithms for process optimization, predictive maintenance, or intelligent resource allocation, combining classical AI methods with quantum computing to achieve higher efficiency and adaptability. Furthermore, we are particularly interested in contributing to learning and knowledge transfer within the consortium by developing frameworks that make hybrid quantum-AI solutions accessible and applicable across industrial domains.

Contact details

Laura Bies

Submitted on 2025-10-30 11:58:26

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