Principal Investigator: Josep Escrig
Email: josep.escrig@i2cat.net
Web: www.i2cat.net
Brief Theme Description:
We are seeking a researcher with a strong background in both Artificial Intelligence and Quantum Technologies, or with deep expertise in one of these fields and a strong commitment to developing expertise in the other. This fellowship offers a unique opportunity to initiate and lead a novel research topic at the intersection of these two pioneering areas.
The appointed fellow will conduct research on how quantum computation can be leveraged to accelerate AI, with potential topics including:
- Designing new classical neural network architectures that can be trained efficiently on quantum computers
- Developing new paradigms for quantum neural networks beyond variational quantum circuits
- Formulating optimization problems as QUBO models for quantum solution methods
In addition, the fellow will explore how AI can reveal, optimize, and enhance functionalities within Quantum Technologies. Research directions in this topic may include:
- Developing advanced quantum communication protocols using AI
- Applying AI-driven techniques to design and optimize quantum circuits for targeted applications
- Applying AI to detect anomalies in quantum communication systems
This fellowship also provides exceptional opportunities to build collaborations with leading research institutions and industry partners, helping bridge fundamental research with practical applications. The fellow will play an active role in initiating and nurturing these partnerships, contributing to advances in the rapidly evolving field of AI-Quantum integration and laying the groundwork for impactful, long-term collaborations.
Available Infrastructures: ML cluster equipped with GPUs.
Possible Secondments: Opportunities for collaboration and secondment may be available with institutions specializing in Quantum Computing and AI, such as ICFO, UAB, UPV/EHU, or other European universities where we can establish new partnerships.
Keywords: Quantum Computing; Quantum Machine Learning; Quantum Algorithms; Neural Network Optimization; Quantum-AI Integration.
