Collaborative Research: NRT-QL: A Program for Training a Quantum Workforce

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Recent progress in quantum information science and technology (QIST) promises advances that will fundamentally reshape today’s leading technologies, including computing, communications, and sensing. A well-prepared workforce is essential to fulfilling this promise. In response to this critical workforce need, this National Science Foundation Research Traineeship (NRT) award to the Colorado School of Mines (Mines) and San Jose State University (SJSU) supports the development of rigorous, integrated, interdisciplinary training programs preparing both Master’s and Doctoral students for careers in QIST. The program has three components that address key challenges in training a quantum workforce. First, new training materials will be developed to introduce QIST basics to students from different disciplines. Trainees will come from physics, electrical engineering, metallurgical and materials engineering, applied mathematics and statistics, computer science, and quantum engineering. Second, industrial and national lab partners will be engaged to provide trainees access to cutting-edge technologies and research experiences. Finally, student recruitment and mentoring programs, unconscious bias training, ally workshops, and regular climate surveys will be developed to ensure diversity in the QIST workforce. The project will train one-hundred and twenty-five (125) MS and Ph.D. students, including thirty-five (35) fully-funded trainees. These efforts will result in an institutionalized program that produces leaders in QIST for careers in academia, industry, government, and national labs. The research program addresses three grand challenges in quantum technology: (1) How can demonstrable quantum speed-up using existing or near-term quantum computing architectures be achieved? (2) How can materials and electrical engineering interface with quantum technology to provide meaningful advances in device development and fabrication? (3) How can new directions in quantum algorithms advance and challenge the notion that quantum technology can solve problems that are impossible to tackle with conventional technology? These interdisciplinary research challenges require close synergy between fundamental physics, materials science, electrical engineering, and algorithm development. New courses and degree pathways in QIST are being developed at both Mines and SJSU, which include integration of professional skills development into the graduate curriculum. Through classroom training and research, trainees will be exposed to the full range of quantum technology architectures, providing a holistic view of this rapidly developing field. An innovative educational agreement between Mines and SJSU will provide opportunities for students to complete an MS/Ph.D. bridge program from SJSU to Mines. The program will result in a template for QIST graduate education, which will be accessible to STEM students from all backgrounds and types of institutions, increasing diversity in QIST. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.