Haven't read the memoir yet, but after reading John's review http://blog.regehr.org/archives/743 I'm looking forward to it. Good luck at Google Phil.
The Ph.D Grind: A Ph.D Student Memoir
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Re: The Ph.D Grind: A Ph.D Student Memoir
#82Earlier quoted context omitted.
hi matt - wow, i was gonna email you tomorrow, but HN scooped me. re: distilling -- my main intention in writing this memoir wasn't to provide advice, since it's hard for me to determine how much facets of my experience generalize. i do have plans to convert the "lessons learned" section from the epilogue into a talk, though. i have this other article from the beginning of my third year that's more of the "advice" ty…
Oh, that was from you, too? I just read this a few days ago (was actually recommended here on HN [1]) and thought it was terrific. That might be one of my biggest problems in science - I have a hard time memorizing people's names. [1] http://news.ycombinator.com/item?id=4141353
Turns out the author wrote about that problem, too [1].
The advice is mostly on how memorize names when you get introduced personally, but admittedly this is an even more important problem. Recommended read.
Re: The Ph.D Grind: A Ph.D Student Memoir
#83More info on CDE (Code, Data, and Environment) without having to read the memoir: http://www.pgbovine.net/cde.html
Re: The Ph.D Grind: A Ph.D Student Memoir
#84Wow, I can't believe I just read that whole thing. Maybe it was the excellent writing quality or maybe I just find things like this interesting. As someone who just graduated with a B.S. in chemical engineering and will start work toward my PhD in the fall (also in chemical engineering, but will actually involve a TON of programming), this strikes a chord with me. A few takeaways from the article: -The author does no…
I'm also in chemical engineering and am looking to integrate programming into my work in grad school. What did you find to work on that's programming related?
Find a grad school with access to a supercomputer. There's a lot of fun ChemE problems that require one of these to solve. Simulating classical or quantum systems (molecular dynamics) takes a lot of algorithmic knowledge from CS and a lot of chemistry knowledge to understand the principles. Then the engineering knowledge is for scaling it up so that you can make something practical with your results.
Re: The Ph.D Grind: A Ph.D Student Memoir
#85Ten mins on the website and this strikes me as all being very "needy". I'm still struggling to understand why everyone feels these type of "little ole me" stories are so fantastic. (It's not the author's first either...) Just wanted to offer the counter opinion. Each to his own...
I agree, this seems to be the story of many academics.