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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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. The projects may also include to tackle benchmarking problems such as SAT, image processing, graph theories, boson/fermion sampling by applying classical machine/deep learning, neural network techniques and
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, model and simulate physical processes, and engage in productive discussions with theoretical quantum physicists. Demonstrated programming skills for data acquisition and processing, e.g., Python, Matlab
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contribute to the collaborative TQT research community. Principal Investigator: Na Young Kim Project: Carbon Nanotube (CNT) Quantum Electronic Devices Research Area: CNT material growth/processing and device
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contribute to the collaborative TQT research community. Principal Investigator: David Cory Project: Develop improved processes for the growth of high-quality superconducting films with applications to quantum