LenielJerron

I only spend one hour a week in my office for my office hour.

Looking at my calendar from this past semester I was in 3 courses, which each met for 3 hours had 8-10 hours of homework each week. I attended 4 weekly seminars (1 of which I was helping organize; two of which I presented in some weeks). I taught one course which met for 4 hours, double that for class prep. I had 5 hours regularly scheduled in the tutoring center, plus an office hour. I'm slow at grading, so it often took me 4-6 hours per week. Plus an hour a week for my advising meeting, and we're at 60 hours before I even begin talking about when I'm doing my own research - I typically try to devote my weekends and also Thursday afternoons in their entirety to either reading math books of interest to me or papers of interest to me (I do the rest of that stuff MTWF).

So it's not quite 90 hours a week every week. There are weeks when the tutoring lab was shortstaffed so I needed to pick up an extra three hours there. There were times when I would proctor a 3-hour exam. There were lots of severe injuries in my department this semester so I've covered people's classes too. So there were a lot of 90 hour work weeks just due to the structure of everything, but I guess saying that every week is a 90 hour week is an exaggeration. I don't think I've worked fewer than 75-80 hours a week all semester though.

Yes, my bad, I get all the TLAs mixed up.

Paul Erdos got his PhD in mathematics when he was 20 years old. If you wanted to name a famous academic without a PhD, you should have gone with Freeman Dyson.

But yes, I need to not starve to death in case I need to leave my program. That's why I mentioned jobs.

How broadly do you dislike programming?

After undergrad, it seemed like I had two career paths. I could either apply for PhDs in mathematics, work 90 hours a week for 19k/year in a state a thousand km away from anyone I've ever known; or I could have tried for a cushy entry-level coding job making 6 figures starting salary in an area close to all my friends from undergrad, and working something normal like 40 hours a week. I chose the former.

I am currently doing what little coding I currently am in an effort to get it over and done with ASAP. My plan is to never write another line of code again once I'm done with my numerical analysis courses.

Again, I don't think I can personally work for military contractor companies like Boeing, Northrup, etc.

In undergrad I did a project on harmonic analysis and wavelets, with some attention having been paid to the signal processing applications. (And by that I mean I learned enough to say 'this has applications in the fields of signal processing and image compression' in the abstract). But at this point it's years ago and I don't remember too much.

I took seven computer science courses as an undergraduate, including three that were programming courses designed for people who would go on to be professional programmers (intro, intermediate, advanced programming). I also took other CS courses that included programming components. Every single task that was just, "please program tetris" or something of that sort, I loathed every second of it.

I will not like programming.

Introductory QM is for undergrads, who also know next to nothing about QM, and I'd bet there are plenty of profs who'd like to unload that job and get back to their desks

Yes, so the job would be given to physics grad students. Which I do not know enough physics to apply to be.

If I'm in a position where I'm being thrown out of my grad program with just a masters, I'm not then going to turn around and say, "well, time to do it all over again, this time with a field I'm less passionate about!"

I will never work for an insurance company. And just saying "the government" is so vague and nebulous as to be meaningless; at least in the US where I am I think it's mostly either military/'defense' stuff, or essentially spying on people. Neither of which I'm comfortable doing.

I've never heard of random facilities, but it warrants looking into given all of the things that you've mentioned. I'm not interested in all of these things, but it definitely sounds like it has a lot more to offer than most other "mathy" jobs. You also say "more abstract things like proofs", but proofs are the entirety of what math is if you have a math degree.

Electrical engineering is its own discipline, separate from math. Unless I go back to undergrad and study EE from scratch, I will never be competitive in that job market against people who have specialized degrees in it.

I don't know quantum physics though. It involves a lot of math, but it also involves a lot of physics which I don't know. It's something that I'd like to learn at some point, but right now I just don't have the available bandwidth to learn it - and I definitely can't teach something I don't know.

When I was in undergrad I did debate, and a term that was used to describe the debate topics was "a solution in need of a problem". I think that that very often characterizes the tech industry as a whole.

There is legitimately interesting math going on behind the scenes with AI, and it has a number of legitimate, if specialized, use-cases - sifting through large amounts of data, etc. However, if you're an AI company, there's more money to be made marketing to the general public and trying to sell AI to everyone on everything, rather than keeping it within its lane and letting it do the thing that it does well, well.

Even something like blockchain and cryptocurrency is built on top of somewhat novel and interesting math. What makes it a scam isn't the underlying technology, but rather the speculation bubbles that pop up around it, and the fact that the technology isn't being used for applications other than pushing a ponzi scheme.

For my own opinions - I don't really have anything I don't say out loud, but I definitely have some unorthodox opinions.

• I think that the ultra-convenient mobile telephone, always on your person at all times, has been a net detriment societally speaking. That is to say, the average iPhone user would be living a happier, more fulfilling, more authentic life if iPhones had not become massively popular. Modern tech too often substitutes genuine real-in-person interactions for online interactions that only approximate it. The instant gratification of always having access to all these opinions at all times has created addictions to social media that are harder to quit than cocaine (source: I have a friend who successfully quit cocaine, and she said that she could never quit instagram). The constantly-on GPS results in people not knowing how to navigate their own towns; if you automate something without learning how to do it, you will never learn how to do it. While that's fine most of the time, there are emergency situations where it just results in people being generally less competent than they otherwise would have been.

• For the same reason, I don't like using IDEs. For example when I code in java, the ritual of typing "import javafx.application.Application;" or whatever helps make me consciously aware that I'm using that specific package, and gets me in the headspace. Plus, being constantly reminded of what every single little thing does makes it much easier for me at least to read and parse code quickly. (But I also haven't done extensive coding since I was in undergrad).

• Microsoft Office Excel needs to remove February 29th 1900. I get that they have it so that it's backwards compatible with some archaic software from the 1990s; it's an annoying pet peeve.

• Technology is not the solution to every problem, and technology can make things worse as much as it can make things better. Society seems to have a cult around technological progress, where any new tech is intrinsically a net good for society, and where given any problem the first attempted solution should be a technological one. But for example things like the hyperloop and tesla self-driving cars and so forth are just new modern technology that doesn't come anywhere near as close to solving transportation problems as just implementing a robust public transit network with tech that's existed for 200 years (trains, trolleys, busses) would.