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Quantum Talent Neural Network

Posted on August 29, 2022, By Brian N. Siegelwax

What matters, and by how much?

Quantum talent is like an artificial neural network: everything has a weight. Also, every job specification has its own model, so the weights for a quantum algorithm developer role are different than the weights for a software engineering role.

For example, a quantum algorithm developer role probably requires a PhD. Postdoc work is heavily weighted. Your PhD thesis is heavily weighted. And, how about that summer school you attended? Compare the time and effort of a summer school to the time and effort of a PhD, and there, sadly, is your answer.

A software engineer, on the other hand, might get by with an undergraduate degree. But, let’s imagine you’re a software engineer who has worked three years at some random company, you had a six-month internship in college, and you have a personal project on GitHub. If a job requirement is to be proficient in C/C++, for example, where do you suppose that experience would be most heavily weighted?

Think about formal education this way: your Masters degree in physics greatly outweighs some physics book I read in my free time. And think about work experience this way: the use case you’ve developed for a client greatly outweighs the mathematics I worked out for some textbook algorithm.

I’m writing this because I regularly speak with job seekers about building their CVs for the future. It’s important to keep in mind this weighting system, because you can spend considerable time building experience that carries very little weight. It would behove you to build experience in the most impactful way possible.

Brian N. Siegelwax


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