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to guide experimental design and validate computational predictions Develop innovative machine learning and statistical models to characterize epigenomic heterogeneity and treatment resistance mechanisms
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that change! Qualifications The position requires a PhD degree in electrical, computer or biomedical engineering, computer science, or a closely related area. The successful candidate is expected to develop
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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contribute to the collaborative TQT research community. Principal Investigator: Na Young Kim Project Name: Solid-state analog Optimization Solver and Quantum Machine Learning (Theory) Research Area