Quantum System Performance Monitoring Intern 2027

Introduction

At IBM Research, we are the innovation engine of IBM. Exploring what’s next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You’ll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world.

Your role and responsibilities

You will join a team of scientists working to improve the performance, stability, and availability of quantum computing systems through automated monitoring and calibration.

In this role, you will help develop and improve techniques for identifying quantum processor performance drift and degradation, making automated decisions about when to recalibrate or take other actions, and optimizing system parameters. Depending on your background and the needs of the project, this may include applying machine learning and AI techniques, statistical analysis, optimization methods, or other data-driven approaches to monitoring and calibration.

Required technical and professional expertise

• Undergraduate-level familiarity with quantum physics and quantum computing, Python programming, numerical analysis and statistics.

Preferred technical and professional experience

• Graduate-level familiarity and/or hands-on real-world experience with many of the above

• Hands-on experience with experimental quantum systems, quantum-device characterization, or calibration

• Experience using the Qiskit python package

• Experience developing or applying machine-learning, statistical, or optimization methods to experimental or time-series data

• Familiarity with anomaly detection, statistical inference, automated control, or parameter optimization

• Experience working with large experimental datasets or data-analysis pipelines

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.