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On the Transience of the Neuroscience PhD
As a hiring manager, I’ve seen an awful lot of resumes over the past few years. My positions have tended to have titles like “data scientist”, “decision support analyst”, and “business analyst”, with job descriptions talking about analysis and statistics and helping people understand data and stuff like that.
Every posting has received a LOT of neuroscientist applicants.
Don’t get me wrong; we get applications from all backgrounds, at all levels of experience. However, I’ve noticed that a disproportionately high number of applicants have neuroscience backgrounds. As someone with a neuroscience PhD1 myself, I find this striking.
Neuroscience has a huge draw: it’s cool. The technology is sexy, the research is fascinating, and the imagined potential is incredible. Understand thought! Figure out how the mind works! Visualize learning! Many people enter the field hoping to understand—and build!—sexy cool technology. Furthermore, the field requires expertise from every background, which means that it’s open to virtually anyone. When I was doing my PhD, we had people coming from computer science, biology, mathematics, psychology, electrical engineering, and chemistry, just to name the ones I remember offhand. Everyone has a lot to learn, so the field is built to train everyone, which decreases the barrier to entry.
Even beyond the research, we’re finally approaching the point where some of the concepts are being used in real life. We’ve managed to build a computational model of the brain. There have been a number of stories about the application of brain imaging to the field of lie detection, often in legal cases. We’ve seen some ridiculously cool videos of monkeys controlling robotic arms using their mind, and that technology has helped paraplegic and quadraplegic wheelchair users drive wheelchairs using brain activity. Heck, there are even toys that have been developed using this technology, and enterprising developers can simply buy a headset and use the company’s API to roll your own games.
The problem is that this is both a really old field and a really, really young one. Neuroscience as a field has been studied since the 1800’s. At this point, some parts of the brain are very well understood. That said, you can see from the above links that neuroscience is just now entering mainstream, and even that adoption has been super slow. The fascination is there, the promise is there, but the breakthrough moments are alway just… around… the… corner. The technology works, but just barely. Doing research is hard enough; getting the tools and techniques to work well enough to be a commercial success is near impossible. This realization hits people at different times, but when it hits, my sense is that people tend to quickly get frustrated. This is followed by a quick exit from the field, never to return.
I’m speaking for myself, of course. I don’t presume to know why the majority of neuroscience PhDs leave the field. That said, for many, they enter hoping to learn something fascinating, and leave with the realization that not only is that promise not ready, no one knows when it will be. At the end of the day, there are only a tiny handful of neuroscience-related jobs out there, and academia is definitely not for everyone. When the promise is just a dream, it’s not surprising that people leave when they wake up.
Actually, biomedical engineering, with focus in neuroscience, but whatever. ↩︎