Now, I started a PhD (on a full time research position) and I feel the same. Probably I would have jumped ship last year if it wasn't for Covid (which made unemployment a pretty bad situation) but now I feel too invested and yet don't know what do too otherwise, i.e. work looks to me like the classic "find me a rock"-problem described there and I'm probably burned out a little.
My supervisor wants to do ML on materials science and since a lot of it has been said and done (and is horrid...), he wanted to add some secret buzzword sauce. Unfortunately he has no idea about ML and what he wants to achieve, he isn't even able to tell me a question I should answer plainly in text. It always goes back to 20min "talks", where he assures me of my good work and asks some questions, a clueless reviewer in peer review would come up (i.e. produce a graphic of X, where X is not relevant to the problem, but related and might be nice to check out, to be 110% sure...).
Disclaimer: if one needs a PhD-dropout physicist with a bit of python and .NET (and a solid understanding of Linux as run in HPC) and an idea about most of the other classic ecosystems, tell me! (no adtech, weapons or cars)
Would you be interested in working in quantitative finance in London? We're hiring (remotely for now, but you'd be expected to work in London probably later this year).
We have lots of PhDs (physics, maths, etc - not exclusively though, I only have a master's in maths) and aren't particularly looking for a finance background, so you're pretty much a classic interview candidate. (Finance knowledge or interest is obviously a plus.) Interviews would be on a combination of general maths, stats, finance, ML and programming - whatever subset you're strongest in.
To sell the role a bit - we work on algorithmic trading, but I probably can't say too much more than that. I'm really enjoying working here, the environment's a lot like hanging out at uni with my nerdy friends and the work is interesting and free of bullshit. Project turnaround time is quick.
Please let me know if you'd be interested in hearing more about this. You can reach me at my_email@wauchope.net, but instead of my_email it's dax.
My supervisor wants to do ML on materials science and since a lot of it has been said and done (and is horrid...), he wanted to add some secret buzzword sauce. Unfortunately he has no idea about ML and what he wants to achieve, he isn't even able to tell me a question I should answer plainly in text. It always goes back to 20min "talks", where he assures me of my good work and asks some questions, a clueless reviewer in peer review would come up (i.e. produce a graphic of X, where X is not relevant to the problem, but related and might be nice to check out, to be 110% sure...).
Disclaimer: if one needs a PhD-dropout physicist with a bit of python and .NET (and a solid understanding of Linux as run in HPC) and an idea about most of the other classic ecosystems, tell me! (no adtech, weapons or cars)