Quantum Device Researcher

About The Company (Industry & Sector)

Quantum Computing, Artificial Intelligence and Semiconductor Engineering

• Model coupled superconducting-qubit systems, building Hamiltonian-level descriptions and validating them through large-scale numerical simulations focused on error-correction performance.
• Develop and optimise qubit-control schemes in close collaboration with processor-design engineers, informing architecture improvements.
• Design simulation workflows and computational tools to predict coherence times, gate fidelities and other key device metrics.
• Create experimental protocols and analysis pipelines for quantum-state & process tomography, feeding results back into theoretical models.
• Publish findings in peer-reviewed venues and author technical reports that guide design-of-experiments (DoE) and roadmap decisions.
• Champion a culture of rigorous peer review, knowledge-sharing and cross-functional collaboration within the quantum-hardware programme.
  

Skills & Qualifications

Must-Have

• MSc/M.Tech/PhD in Physics, Electrical Engineering or related field with strong quantum-mechanics foundation.
• Deep knowledge of Hamiltonian engineering, circuit QED and superconducting-qubit error-correction schemes.
• Expertise in numerical methods & computational modelling of quantum circuits; proficiency with Python-based quantum platforms (e.g., QuTiP, Qiskit, Cirq).
• Experience designing protocols to measure coherence times, gate fidelities and tomography.
• Demonstrated record of peer-reviewed publications in quantum technology and strong problem-solving & communication skills.
  

Preferred

• Familiarity with bosonic codes, autonomous error-correction and advanced value-engineering techniques.
• Experience writing analytical reports to shape DoE and experimentation roadmaps.
• Prior work on GPU-accelerated simulators or distributed-computing pipelines for large-scale quantum modelling.
• Contributions to open-source quantum-software libraries or standards bodies.
• Exposure to hybrid AI-quantum workflows or domain-specific optimisation (life-sciences, finance, materials).