Collaborative research: cybertraining: implementation: medium: building a dual-expertise workforce in quantum computing and healthcare through dual-state collaboration

The National Science Foundation Office of Advanced Cyberinfrastructure awarded Kent State University $244,874 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a domain-driven cybertraining program connecting quantum computing expertise with healthcare and biomedical applications.

The project establishes a sustainable training framework through three integrated training thrusts. The first thrust creates modules linking healthcare problem formulation with quantum concepts and algorithms, including quantum-compatible data representations and applications in molecular modeling and diagnostic analysis. The second thrust develops modules on quantum software productivity, portability, and reproducibility, covering cross-platform program translation, auditable workflow construction, and uncertainty-aware evaluation of noise, drift, and hardware variability. The third thrust creates application-driven modules guiding practical implementation of quantum technologies in healthcare domains.

The project produces openly shared training modules, software tools, datasets, tutorials, and curriculum materials designed to broaden access to quantum education and extend workforce development benefits beyond participating institutions. Performance occurs at Kent State University in Kent, Ohio, with a period of performance from August 1, 2026, through July 31, 2030.

Abstract

This project addresses the growing national need for a quantum computing workforce equipped not only with theoretical knowledge but also with practical skills for applying quantum technologies to healthcare and biomedical research. Quantum computing creates new opportunities in areas such as molecular modeling, diagnostic analysis, drug discovery, biomedical imaging, and clinical decision support. By establishing a domain-driven training program that connects quantum computing with real-world healthcare applications, this project promotes the progress of science, strengthens national competitiveness in emerging quantum technologies, and supports future innovation in health and medicine. The openly shared training modules, software tools, datasets, tutorials, and curriculum materials support long-term workforce development, broaden access to quantum education, and ensure that the benefits extend well beyond the participating institutions. The primary goal of this project is to establish a sustainable training framework for developing dual expertise in quantum computing and healthcare applications. To achieve this goal, the team of researchers develops a domain-driven cybertraining program organized around three integrated training thrusts. First, the project creates modules that help participants connect healthcare problem formulation with quantum concepts and algorithms, including quantum-compatible data representations and applications in molecular modeling and diagnostic analysis. Second, the project develops modules on quantum software productivity, portability, and reproducibility, including cross-platform program translation, auditable workflow construction, and uncertainty-aware evaluation of noise, drift, and hardware variability. Third, the project creates application-driven modules that guide participants in building complete quantum-classical workflows for healthcare use cases, including protein structure prediction, quantum-ready dataset design, and DNA and RNA therapeutics modeling. Together, these efforts deliver a reusable and scalable training program that combines rigorous instruction, hands-on practice, open-source resources, simulated and real quantum hardware, and healthcare-relevant applications, positioning participants to contribute to the national quantum workforce and to the responsible use of quantum computing in biomedical research. 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.- subawards are not planned for this award.