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Automation of Qubit Characterization with Machine Learning
Master internship - Leuven | More than two weeks ago
Automation of Qubit Characterization with Machine Learning
Qubit characterization is composed of a number of steps each require a dedicated measurement based on initial sweep, averaging and voltage level parameters. While some of these parameters can be set programatically, some still require manual intervention in case of new previousely unmeasured qubits. A student will explore in this internship how machine learning can be levaraged to eliminate the need for manual intervention and make qubit characterization fully automatic. This internship is focused on measurement software development in python.
Type of internship: Master internship
Duration: 3months
Required educational background: Computer Science
University promotor: Kristiaan De Greve (KU Leuven)
Supervising scientist(s): For further information or for application, please contact Anton Potocnik (Anton.Potocnik@imec.be)
The reference code for this position is 2026-INT-174. Mention this reference code in your application.
Only for self-supporting students.
Applications should include the following information:
- resume
- motivation
- current study
Incomplete applications will not be considered.