Quantum Measurement Engineer - DeepRec.ai

12 ago - Lucca
DeepRec.ai

Quantum Measurement Engineer Seeking an experienced Quantum Measurement Engineer to develop and optimise high-fidelity measurement and control systems for superconducting quantum processors. The role involves designing experimental measurement infrastructure, improving qubit performance, automating experiments, and collaborating across hardware and software teams to support the development of scalable quantum computing systems.

Responsibilities

Design and optimise qubit readout and control systems for superconducting quantum hardware.

Develop and execute qubit characterisation protocols (e.g. T₁, T₂, Ramsey, echo, randomized benchmarking, readout fidelity, crosstalk).

Improve measurement fidelity and signal-to-noise performance within hardware constraints.

Develop and maintain experimental control software using Python and laboratory instrumentation.

Analyse experimental data and compare results with theoretical models and simulations.

Collaborate with multidisciplinary engineering and research teams to improve device performance.

Support the development of scalable measurement architectures and laboratory automation.





Document experimental methods, results, and technical findings.

Requirements

MSc or PhD in Physics, Applied Physics, Electrical Engineering, or a related discipline.

Significant hands‑on experience working with superconducting qubits or similar quantum hardware.

Experience with microwave electronics and measurement equipment (e.g. IQ mixers, amplifiers, VNAs).

Strong understanding of quantum measurement techniques and qubit decoherence.

Experience operating cryogenic systems, including dilution refrigerators.

Proficiency in Python for experiment control and data analysis.

Familiarity with laboratory automation and experimental measurement frameworks.

Ability to troubleshoot complex hardware and software systems.

Benefits

Competitive salary and benefits package.

Equity or share option opportunities.

Flexible and hybrid working arrangements.

Collaborative, merit-based working environment with opportunities for professional growth.

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