By Yuval Boger
When companies recognize that quantum computing has the potential to dramatically transform their business, they often seek to hire quantum information science PhDs to staff their quantum activities. The thought is that such PhDs are quantum experts and are equipped with knowledge and experience that can help accelerate a company’s quantum program. But would hiring many such PhDs be a realistic approach? What might be good alternatives?
One challenge with hiring quantum PhDs is that there are not enough of them. McKinsey’s June ‘22 Quantum Technology Monitor reports that there were 851 active quantum computing job postings in Dec ‘21, yet annually only 290 quantum technology graduates are available to fill these positions without requiring significant training. The same report notes that only 12 universities in the US (and a total of 29 universities worldwide) offer a quantum technology master’s degree, so it’s unlikely that the number of graduates will increase as quickly as the need for their services.
But that’s not the only concern. Companies build quantum teams to explore quantum solutions to their specific challenges – option pricing, chemical simulation, supply chain optimization, etc. How quickly would these quantum graduates pick up the intricacies of the business? Even if such a graduate became well-versed in high-end finance, for example, they might not have the personal relationships and interpersonal skills to navigate company politics and build organizational support for their efforts. They also often lack relationships with peers in the industry and thus might be limited in their ability to leverage lessons learned in other organizations.
An alternative could be up-skilling, providing quantum training to in-house scientists and engineers that already understand the business and are well-connected in the organization as well as in their respective industries. Quantum computing is a hot topic and, in my experience, many would be highly motivated to participate in quantum training. Many online (sometimes free) courses are available for both beginners and advanced users. Additionally, the emergence of higher-level libraries and abstraction layers makes it easier to create useful quantum software without mastering the fine details of how quantum computers are built or resorting to intricate low-level coding. Often, quantum computing efforts sometimes grow from the bottom up, not by executive edict, and motivated employees just need permission to spend more time learning and exploring. Last, up-skilling promotes employee retention and job satisfaction.
Another option is to plug the skills gap using consulting companies. Firms like BCG or Deloitte can perform two types of functions. The first – educating executives, identifying promising use cases, and providing industry benchmarks – can be very useful to accelerate a company’s quantum program. The second – actually writing quantum computing code, whether by generalist companies or those specializing in quantum computing – can be a mixed blessing. They might provide trained, able consultants, but organizations sometimes worry about IP-sharing arrangements or the ability to develop their workforce when relying on outside parties.
Last, an emerging option is quantum API marketplaces. Just like Google provides an API for finding the best route between two points, quantum API marketplaces provide “pay per use” quantum algorithms for optimization, random number generation, and more. They potentially allow faster exploration of use cases without the burden of coding sophisticated algorithms.
I’m not recommending shying away from hiring quantum PhDs but rather exploring an intelligent mix of these alternatives. Quantum computing is too important to ignore. Don’t slow down the progress by exclusively relying on outside talent.
Yuval Boger is a quantum computing executive. Known as the original “Qubit Guy,” he most recently served as Chief Marketing Officer for Classiq.
September 1, 2022