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Boeing prize will honor early quantum researchers this December

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August 10, 2026 by Ivy Delaney

Boeing is now accepting applications for the 2026 Boeing Quantum Creators Prize, recognizing early-career researchers who are advancing quantum information science and engineering. A $3.5 million investment from Boeing in 2023 fueled an expansion of the program, which has already propelled 63 past honorees into roles at companies like IBM and Google Quantum AI, or faculty positions at institutions including UC Berkeley, Yale, and Stanford. The 2026 honorees will present their work at the Q2B x Chicago Quantum Summit, held December 8, 10 at Marriott Marquis Chicago and McCormick Place.

2026 Boeing Quantum Creators Prize: Application and Eligibility

Boeing’s commitment to quantum information science is demonstrated by a $3.5 million investment in 2023, which facilitated an expansion of the Boeing Quantum Creators Prize program and broadened its reach to early-career researchers. The prize recognizes individuals pushing boundaries in quantum information science and engineering, with the 2026 cohort set to be announced and honored this December. Tenure-track and tenured faculty are not eligible for consideration, focusing the prize on those still establishing their careers.

Awardees will receive a trophy, travel reimbursement to the Q2B x Chicago Quantum Summit, and a $3,500 monetary prize, provided they meet legal requirements for eligibility. The program’s impact extends beyond immediate recognition; 63 Boeing Quantum Creators honored between 2021 and 2025 have secured positions at leading institutions and companies.

These include roles at IBM and Google Quantum AI, as well as faculty appointments at the University of California, Berkeley, Yale University, and Stanford University. One of six previous winners was highlighted last year, demonstrating the program’s role as a career launchpad. The application deadline, including required letters of recommendation, is September 18, 2026.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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