GoKawiilThis guide is patterned after my “Doing well in your courses”, a post I wrote a long time ago on some of the tips/tricks I’ve developed during my undergrad. I’ve received nice comments about that guide, so in the same spirit, now that my PhD has come to an end I wanted to compile a similar retrospective document in hopes that it might be helpful to some. Unlike the undergraduate guide, this one was much more difficult to write because there is significantly more variation in how one can traverse the PhD experience. Therefore, many things are likely contentious and a good fraction will be specific to what I’m familiar with (Computer Science / Machine Learning / Computer Vision research). But disclaimers are boring, lets get to it!
Preliminaries
First, should you want to get a PhD? I was in a fortunate position of knowing since young age that I really wanted a PhD. Unfortunately it wasn’t for any very well-thought-through considerations: First, I really liked school and learning things and I wanted to learn as much as possible, and second, I really wanted to be like Gordon Freeman from the game Half-Life (who has a PhD from MIT in theoretical physics). I loved that game. But what if you’re more sensible in making your life’s decisions? Should you want to do a PhD? There’s a very nice Quora thread and in the summary of considerations that follows I’ll borrow/restate several from Justin/Ben/others there. I’ll assume that the second option you are considering is joining a medium-large company (which is likely most common). Ask yourself if you find the following properties appealing:
Freedom. A PhD will offer you a lot of freedom in the topics you wish to pursue and learn about. You’re in charge. Of course, you’ll have an adviser who will impose some constraints but in general you’ll have much more freedom than you might find elsewhere.
Ownership. The research you produce will be yours as an individual. Your accomplishments will have your name attached to them. In contrast, it is much more common to “blend in” inside a larger company. A common feeling here is becoming a “cog in a wheel”.
Exclusivity. There are very few people who make it to the top PhD programs. You’d be joining a group of a few hundred distinguished individuals in contrast to a few tens of thousands (?) that will join some company.
Status. Regardless of whether it should be or not, working towards and eventually getting a PhD degree is culturally revered and recognized as an impressive achievement. You also get to be a Doctor; that’s awesome.
Personal freedom. As a PhD student you’re your own boss. Want to sleep in today? Sure. Want to skip a day and go on a vacation? Sure. All that matters is your final output and no one will force you to clock in from 9am to 5pm. Of course, some advisers might be more or less flexible about it and some companies might be as well, but it’s a true first order statement.
Maximizing future choice. Joining a PhD program doesn’t close any doors or eliminate future employment/lifestyle options. You can go one way (PhD -> anywhere else) but not the other (anywhere else -> PhD -> academia/research; it is statistically less likely). Additionally (although this might be quite specific to applied ML), you’re strictly more hirable as a PhD graduate or even as a PhD dropout and many companies might be willing to put you in a more interesting position or with a higher starting salary. More generally, maximizing choice for the future you is a good heuristic to follow.
Maximizing variance. You’re young and there’s really no need to rush. Once you graduate from a PhD you can spend the next ~50 years of your life in some company. Opt for more variance in your experiences.
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