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on developing novel readout techniques for spin quantum dot-based qubits, hybrid QD-cavity systems, and flip-chip technology integration. The project's primary focus is on exploring fast and high-fidelity readout
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these challenges, in close collaboration with our interdisciplinary team and external scientific and industry partners. As part of this process, you will support our master students, publish in scientific journals
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required. Applicants must have obtained their Master's degree by September 2024 A strong foundation in analyzing large datasets and machine learning is highly desirable for this position Proficiency in
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topics and methods. You should: Hold a master's degree in a relevant field, such as Chemistry, Physics, Engineering or similar Have an excellent track record and meet the general admission requirements