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Quantum Initiative

Summer Workshop on Quantum Machine Learning for Complex Science and Engineering Problems

Quantum information and computing technologies are rapidly reshaping scientific discovery, enabling breakthroughs in materials, chemistry, pharmaceuticals and  climate modeling. To ensure U.S. leadership in this emerging field, the next generation of scientists, engineers, and innovators must be trained at the intersection of quantum computing and machine learning, Quantum Machine Learning (QML).

NC State University, a national leader in quantum engineering and semiconductor innovation, will host the first “Summer Workshop on Quantum Machine Learning for Complex Science and Engineering Problems”. This five-day intensive program, hosted by the NC State Quantum Initiative, will bring together leading experts and emerging researchers to explore foundational aspects and advanced hybrid quantum-classical methods for solving real-world scientific challenges in the field of chemistry and materials.

The event is strategically designed to accelerate education, collaboration, and workforce development across academia, national labs, and industry partners in the Research Triangle and beyond.

Interest Form

Overview

  • Date: June 1-5, 2026
  • Location: Main Campus, NC State University, Raleigh, NC
  • Daily Schedule: 8:00 AM – 4:30 PM 

Participants will develop proficiency in QML theory, algorithms, and quantum programming frameworks while applying methods to real scientific and engineering problems.

Technical Focus Areas

This summer school covers both foundations and emerging research directions in QML,
including:

  • Foundations of Quantum Computing and QML
  • Learning Theory in QML Models
  • Quantum Algorithms for Data Analytics
  • Fault-Tolerant QML Algorithms
  • Quantum Computing Architectures and Error Correction
  • Federated QML for Drug Discovery and Healthcare
  • Quantum-enabled ML for molecular and materials simulation
  • QML Applications in Sensing and Optimization

Who Should Attend?

  • Graduate students and postdocs
  • Faculty and scientific researchers
  • National lab and industry professionals in quantum technologies
  • Anyone seeking cutting-edge training in QML foundation theory and applications.