This is an astoundingly relevant answer to my question and thank you for taking the time to tell your story. I don't have an answer yet but this gives me something to think about. I share the same interests outside of the office and the same feeling you had once the bubble burst. I was hoping to find some advice on how I could turn the experience I did have into something beneficial to a potential employer—such as the NPS—but thinking long and hard about what I'm good at, want to do, and who might be able to help me get there is probably a more feasible route.
I'd consider also how you can pivot slightly rather than completely. Coming out of my undergrad degree I had absolutely zero interest in writing boiler plate style software suited-up in a large company. Instead I took on jnr research positions in other fields like earth sciences as a research assistant, working with satellite data and high throughput laser scanning. Essentially the computer/robotics guy for people not capable of that but with grand ideas. You can find these sorts of jobs on NewScientist or Nature jobs listings, academics are incredibly accepting of computer literate field swappers. Eventually I realised a PhD was essentially the only way to have freedom in the space of research. So I found the most general explorative course I could, which at the time was a new PhD centre training a large cohort (60+ students over 8 years) in complexity sciences. The experience of being around a load of smart people from various backgrounds all working on interesting problems cannot be under estimated as a morale boost. I now also have a wide network of friends doing cool stuff I can always rely on in a pinch for perhaps finding fun work. The course was super rapid switching between subjects with maths covered the whole time. It gave me exposure to most university departments and the sorts of big problems everyone had. Eventually I came across protein structures and molecular biology which was only something I only had a rough understanding of coming from computer science, self studying the biology behind genetic algorithms. The realities of that field have completely sucked me in forever, like nothing I've really found before. I had a misguided try at doing some robotics before settling on molecular biology. But now post PhD I get to work in companies that are doing really interesting stuff, and on software that's relatively creative and cutting edge to develop compared to what I could have been working on post undergrad. Not all software has to give you that trapped dead end feeling. I've recently switched jobs simply because what I was working on wasnt quite engaging enough and I felt trapped by the higher rents that tend to be common where techy jobs are aplenty. But you really dont have to accept this at all once you have some experience and a network of contacts developed.
> But now post PhD I get to work in companies that are doing really interesting stuff
Isn't it crazy hard to get hired for a research position? I was told in the past that just because you had a PhD didn't mean you would automatically be able to find a job doing interesting research.
> The realities of that field have completely sucked me in forever, like nothing I've really found before.
>Isn't it crazy hard to get hired for a research position? I was told in the past that just because you had a PhD didn't mean you would automatically be able to find a job doing interesting research.
It's crazy hard to get hired for a permanent research position in academia at a university people will have heard of. In science and engineering <10% of people go on to PhD and <10% of those PhDs who graduate find a permanent position. If you don't feel like you were the top 1% of your year at uni, then its going to be harder, or you've been under appreciated and are good at research rather than being taught. So yeah to remain in academia being paid little actually takes you being incredibly good. But getting an operational research job in something like an innovation or RnD department, in a company, is about as hard as getting any other job once you have some experience, and are qualified for the work. A PhD is not at all required though. But in life sciences its kind of important right now. The main issue of work being "interesting" is probably if you have directly relevant experience or not, which is a lot less likely as a researcher. If you're like me though and can get interested in almost anything then pragmatism wins. Plenty of knowledge and research skills are completely transferable. Getting a PhD is not really about skill or ability its an endurance race that very few people even sign up for and even less finish. By definition finishing the race means you are capable of doing it. It's a trial by fire.
Nothing is automatic in life. The number of hopelessly incompetent people with a PhD is only slightly less than the number with an undergrad degree or without any higher education. That doesn't change. But yeah if someone sucks, they suck. That's never something that can be overcome with a piece of paper. But a PhD at the very least usually represents a level of dedication to trying to make yourself suck less that others were unwilling to sign up for. That's probably about all its ever recognised as. My experience to date is people with a PhD are hugely self starting, and capable of pushing a project along independently. Which is simply a product of being left alone floating in a room for several years expected to solve something independently.
> In what way?
The main way is that I come from an AI background by training. Many of the concepts from that field set you up for sort of reverse engineering how things might be working in molecular biology. It's not that cells and proteins are remotely like computers, but they are doing heavy computation in a strange way and AI is essentially the field of understanding strange computation. The main thing I was interested in when I was doing an AI degree were optimisation problems and specifically genetic algorithms. Turns out evolution of molecular biology -the real thing- is just vastly more interesting and complex in a way you wish you could get genetic algorithms to behave. Better yet is that the alarming rise of biotech to actually manipulate how life works, means for all intents and purposes theoretical work you do in molecular biology can directly become technology. It's basically what I was looking for in AI.
