Research Intern - Next Generation Systems (3 months)

As quantum computing and AI continue to evolve rapidly, a critical frontier is discovering and implementing quantum and hybrid quantum-classical algorithms that significantly outperform their best classical analogues.

This internship focuses on the intersection of quantum optimization algorithms, artificial intelligence, and systems engineering, targeting both near-term devices and future fault-tolerant hardware. We are exploring how AI can accelerate algorithmic development, automate complex experimentation, and help users harness the full power of quantum computing for optimization.

We invite applications from candidates interested in the areas like the following:

• Developing methods for efficiently determining the optimal solver (quantum, classical, AI or hybrid) for complex mathematical optimization problems.

• Designing, benchmarking, and evaluating agentic AI systems to help users and researchers harness quantum optimization algorithms.

• Co-design of hybrid quantum-classical optimization algorithms and the quantum platform to efficiently support novel workloads

This work sits at the cutting edge of quantum computing, agentic applications, and system design, offering the intern a unique opportunity to contribute to advancing the robustness, efficiency, and scalability of next-generation quantum-classical workflows.