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The other solution to the quantum workforce problem

20
September
,
2021

There is widespread agreement that there are not enough quantum information scientists to fill the growing need of companies. As organizations start building quantum computing solutions, they need a trained workforce that can program quantum computers, and such people are hard to come by.

One obvious solution, that is now implemented by MIT, Harvard, USC and other major universities and colleges, is to set up a quantum information science major, a relevant curriculum that can train undergraduates and graduate students. Such was the case with AI/ML several years ago. While these efforts are most welcome, they would take several years to produce enough graduates that are proficient in quantum.

The other solution is to make is simpler to write quantum code. By creating software that focuses on the 'what' rather than the 'how', on what the algorithm needs to achieve rather than how qubits and quantum gates are connected to achieve it, we can make quantum programming more accessible. This is important not just to get more people into quantum, but also to integrate non-quantum experts (such as in machine learning, supply chain, finance or chemistry) into quantum teams.

Yes, you might still need a quantum information scientist to help with high-level design and architecture, to understand the tradeoffs and the academic papers, but you could use many other engineers with quantum knowledge that is not Ph.D-level to fill the team and create useful and sophisticated quantum circuits faster.

There is widespread agreement that there are not enough quantum information scientists to fill the growing need of companies. As organizations start building quantum computing solutions, they need a trained workforce that can program quantum computers, and such people are hard to come by.

One obvious solution, that is now implemented by MIT, Harvard, USC and other major universities and colleges, is to set up a quantum information science major, a relevant curriculum that can train undergraduates and graduate students. Such was the case with AI/ML several years ago. While these efforts are most welcome, they would take several years to produce enough graduates that are proficient in quantum.

The other solution is to make is simpler to write quantum code. By creating software that focuses on the 'what' rather than the 'how', on what the algorithm needs to achieve rather than how qubits and quantum gates are connected to achieve it, we can make quantum programming more accessible. This is important not just to get more people into quantum, but also to integrate non-quantum experts (such as in machine learning, supply chain, finance or chemistry) into quantum teams.

Yes, you might still need a quantum information scientist to help with high-level design and architecture, to understand the tradeoffs and the academic papers, but you could use many other engineers with quantum knowledge that is not Ph.D-level to fill the team and create useful and sophisticated quantum circuits faster.

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