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You will play a critical role in our design, fabrication, and test flywheel as a Data Scientist in the quantum integrated circuit design team. Through comprehensive and robust analysis of large, ever-expanding datasets obtained from existing quantum processors and test devices, you will extract relevant empirical calibrations to improve the accuracy of our processor design and the performance of subsequent generations of processors.

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You will develop software infrastructure to streamline and automate these analyses to accelerate learning cycles. Finally, you will collaborate closely with researchers and engineers across Rigetti to monitor and improve fabrication yield, and improve the models and infrastructure used to predict processor performance from foundry metrology data.

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Key responsibilities include designing and implementing industry-grade software infrastructure in Python to streamline feedback from measurement to the integrated circuit design team, identifying correlations between fabrication metrology data and processor performance through the analysis of empirical datasets, and utilizing techniques and best practices in statistical analysis and machine learning to accurately calibrate various processor design parameters.

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Required qualifications include an undergraduate degree in Computer Science, Physics, Applied Physics, Electrical Engineering, or a related field, 6+ years of experience in data science and statistical analysis in a scientific field, and programming skills in Python for scientific applications.

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XML job scraping automation by YubHub

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