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Joined 5 days ago
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Cake day: December 22nd, 2024

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  • 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.



  • 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.





  • 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.




  • A big issue that a lot of these tech companies seem to have is that they don’t understand what people want; they come up with an idea and then shove it into everything. There are services that I have actively stopped using because they started cramming AI into things; for example I stopped dual-booting with Windows and became Linux-only.

    AI is legitimately interesting technology which definitely has specialized use-cases, e.g. sorting large amounts of data, or optimizing strategies within highly restrained circumstances (like chess or go). However, 99% of what people are pushing with AI these days as a member of the general public just seems like garbage; bad art and bad translations and incorrect answers to questions.

    I do not understand all the hype around AI. I can understand the danger; people who don’t see that it’s bad are using it in place of people who know how to do things. But in my teaching for example I’ve never had any issues with students cheating using ChatGPT; I semi-regularly run the problems I assign through ChatGPT and it gets enough of them wrong that I can’t imagine any student would be inclined to use ChatGPT to cheat multiple times after their grade the first time comes in. (In this sense, it’s actually impressive technology - we’ve had computers that can do advanced math highly accurately for a while, but we’ve finally developed one that’s worse at math than the average undergrad in a gen-ed class!)


  • I don’t know much about how to enter into a relationship online; I know people who have done it, but it’s never been something that I’ve been interested in. However, many of my strongest friendships were made online.

    The trick to making friends online is to not set out with the intention of making friends. It’s paradoxical, I know. What you should do is just find something that you’re interested in, find places online you can talk about them, and try talking about them. Personally I like math, so I met some friends on internet math chatrooms and forums. I like Star Wars, and I made some good friends through talking about Star Wars online.

    Many such places also have a casual conversation place attached. In niche communities where you (a) are already engaging with people with a common interest and (b) there’s few enough people that you will see names and faces regularly, but enough people that the conversation never dies down, eventually you’ll become a known quantity and make friends.