A few thoughts on ML/AI safety which may or may not generalize:
You should read successful candidates’ SOPs to get a sense of style, level of detail, and content c.f. 1, 2, 3.
Ask current EA PhDs for feedback on your statement.
Probably avoid writing a statement focused on an AI safety/EA idea which is not in the ML mainstream e.g. IDA, mesa-optimization, etc.
If you have multiple research ideas, considering writing more than one (i.e. tailored) SOP and submit the SOP which is most relevant to faculty at each university.
Look at groups’ pages to get a sense of the qualification distribution for successful applicants, this is a better way to calibrate where to apply than looking at rankings IMO. This is also a good way to calibrate how much experience you’re expected to have pre-PhD. My impression is that in many ML programs it is very difficult to get in directly out of undergraduate if you do not have an exceptional track-record e.g. top publications, or Putnam high scores etc.
For interviews, bringing up concrete ideas on next steps for a professor’s paper is probably very helpful.
My vague impression is that financial security and depression are less relevant than in other fields here, as you can probably find job opportunities partway through if either becomes problematic. Would be interested to hear disagreement.
A bunch of this definitely does generalize, especially:
“If you have multiple research ideas, considering writing more than one (i.e. tailored) SOP and submit the SOP which is most relevant to faculty at each university.”
“Look at groups’ pages to get a sense of the qualification distribution for successful applicants, this is a better way to calibrate where to apply than looking at rankings IMO. This is also a good way to calibrate how much experience you’re expected to have pre-PhD.”
And if you can pull this off, you’ll make an excellent impression: “For interviews, bringing up concrete ideas on next steps for a professor’s paper is probably very helpful.”
CS majors and any program that’s business relevant (e.g. Operations Research and Financial Engineering) have excellent earning/job prospects if they decide to leave partway through. I think the major hurdle to leaving partway through is psychological?
A few thoughts on ML/AI safety which may or may not generalize:
You should read successful candidates’ SOPs to get a sense of style, level of detail, and content c.f. 1, 2, 3. Ask current EA PhDs for feedback on your statement. Probably avoid writing a statement focused on an AI safety/EA idea which is not in the ML mainstream e.g. IDA, mesa-optimization, etc. If you have multiple research ideas, considering writing more than one (i.e. tailored) SOP and submit the SOP which is most relevant to faculty at each university.
Look at groups’ pages to get a sense of the qualification distribution for successful applicants, this is a better way to calibrate where to apply than looking at rankings IMO. This is also a good way to calibrate how much experience you’re expected to have pre-PhD. My impression is that in many ML programs it is very difficult to get in directly out of undergraduate if you do not have an exceptional track-record e.g. top publications, or Putnam high scores etc.
For interviews, bringing up concrete ideas on next steps for a professor’s paper is probably very helpful.
My vague impression is that financial security and depression are less relevant than in other fields here, as you can probably find job opportunities partway through if either becomes problematic. Would be interested to hear disagreement.
Great advice! Thanks for sharing :)
A bunch of this definitely does generalize, especially:
“If you have multiple research ideas, considering writing more than one (i.e. tailored) SOP and submit the SOP which is most relevant to faculty at each university.”
“Look at groups’ pages to get a sense of the qualification distribution for successful applicants, this is a better way to calibrate where to apply than looking at rankings IMO. This is also a good way to calibrate how much experience you’re expected to have pre-PhD.”
And if you can pull this off, you’ll make an excellent impression: “For interviews, bringing up concrete ideas on next steps for a professor’s paper is probably very helpful.”
CS majors and any program that’s business relevant (e.g. Operations Research and Financial Engineering) have excellent earning/job prospects if they decide to leave partway through. I think the major hurdle to leaving partway through is psychological?