- Number 1 thing is having ~2-3 plausible advisors that you can see yourself working with (by all means fall in love with just one, but keep some optionality)
- Most physics departments allow for 'rotations' during your 1st or 2nd year (while you are taking classes and studying for the qual). Check if the 2-3 plausible advisors will take you as a rotation student
- Check if the grad students are (relatively) happy, especially the 4th-5th years during your open house. Ask them how much help the are getting in career search (good departments take care of their senior grad students)
- I personally didn't care to optimize for locale very much. Don't regret it. PhD is a grind,
you won't have too much time to yourself... and with what you have, I think you can have a vibrant social life at almost any university
- There is some funding anxiety right now (NIH, but surely NSF is not far behind). I would make sure that the labs you are in are well funded. Stanford is better in this regard.
- I would max out your applications to GRFP, NDSEG or whatever the in-vogue PhD fellowships are. It increases your chances of getting into a competitive lab
- You didn't say theory or experiment? If experiment, find out if you are going to spend time in the fab, and make sure you check out the fab. Berkeley nanolab was a shockingly functional shithole (at least when i visited, and i know it caused misery to many friends)
I like his articles, but the artificial constructs sometimes drive me up the wall. After reading through a fairly rudimentary strawman about outcomes defining the difference between obstinacy and persistence, we reach the last paragraph that trades a poorly defined word (persistence) for five poorly defined words (imagination, focus, energy, judgement, resilience)
persistence is also defined by flexibility in thinking, appetite for risk/comfort with uncertainty, low ego. equally useless
I too like these Just So Stories of the Startup Underground, but damn, they come off like Malcolm Gladwell forming a taxonomy of the kids that got it vs the kids that don't.
These are all properties of people, that ebb and flow and change from each problem they are working on. It is more productive to talk about contextualized behaviors over the properties of people.
I've found that properties and other traits in people can be malleable and change over time.
I have tons of personal experiences where a new developer seems very obstinate because they've never had anybody really challenge the way they do things. They get onto a project and suddenly get put in their place by a more senior developer. It might have to happen once, or several times before they start to change how they approach things and become more humble over time.
But I agree, properties of people can change, behaviors you can change for a short time, but you inevitably will regress back to how you normally behave. As such, behaviors tend to be easier to observe and predict.
The marshmellow test was debunked. Turns out like many if these bad experiments when you factor socioeconomic status the test cannot be reproduced. Turns out poor hungry kids just tend to eat free food when its available.
HN downvoting scientific studies... I'm worried that this site has reached its eternal September. A huge loss since reddit went public and killed all real discussion, this was one of the last places with intelligent discourse.
This is a good explanation of “price discovery” on the consumer side.
The added benefit is also that there is price discovery on the Advertiser side. A bulk of advertising is auction based, which allows the advertiser to express their willingness to pay for a given audience.
So in theory, both sides of the transaction can be optimally priced.
- Most physics departments allow for 'rotations' during your 1st or 2nd year (while you are taking classes and studying for the qual). Check if the 2-3 plausible advisors will take you as a rotation student
- Check if the grad students are (relatively) happy, especially the 4th-5th years during your open house. Ask them how much help the are getting in career search (good departments take care of their senior grad students)
- I personally didn't care to optimize for locale very much. Don't regret it. PhD is a grind, you won't have too much time to yourself... and with what you have, I think you can have a vibrant social life at almost any university
- There is some funding anxiety right now (NIH, but surely NSF is not far behind). I would make sure that the labs you are in are well funded. Stanford is better in this regard.
- I would max out your applications to GRFP, NDSEG or whatever the in-vogue PhD fellowships are. It increases your chances of getting into a competitive lab
- You didn't say theory or experiment? If experiment, find out if you are going to spend time in the fab, and make sure you check out the fab. Berkeley nanolab was a shockingly functional shithole (at least when i visited, and i know it caused misery to many friends)
TL;DR - Stanford if research fit is there.