How to do research careers
June 28, 2015 — November 4, 2022
On the details of surviving the environment of academia and adjacent institutions.
1 Post COVID-19 seminars
Yes, research seminars are now even more global. See researchseminars.org.
2 General menus
Making the right moves: A Practical Guide to Scientific Management for Postdocs and New Faculty (Burroughs Wellcome Fund and Howard Hughes Medical Institute 2006)
There is a Q&A site about this, Academia stackexchange
For early career types, classic blog Thesis Whisperer
Read Academic work-life-balance survey to feel like not bothering with academe.
AI research: the unreasonably narrow path and how not to be miserable
How to Become the Best in the World at Something
This is how skill stacking works. It’s easier and more effective to be in the top 10% in several different skills — your “stack” — than it is to be in the top 1% in any one skill.
3 Specific morsels
Go to Yale: An astonishingly small number of elite universities produce an overwhelming number of America’s professors
Alexandre Afonso advises “How academia resembles a drug gang”:
If you are mobile, strategic and concerned with employment conditions, you might want to exploit these differences and avoid the outsider boxes at different stages of your career. This would mean avoiding the UK for your PhD and avoiding Germany after your PhD.
Maxwell Tabarrok, Overfitting In Academia
But our selection criteria do not match with what we want academics to do. The out of sample prediction ability of academics is worse than random and laymen. They know lots about research they’ve already been tested on, but are rarely better than random at guessing the results of experiments in their field that they haven’t seen before. Citations and academic rank do not increase the ability of economists to predict the outcome of economic experiments or political events.
Ten simple rules in good research practice for early career researchers
4 Research prioritization
A current meta-question. One starting point: John Schulman’s Opinionated Guide to ML Research, which discusses stuff like this:
5 Idea-Driven vs Goal-Driven Research
Roughly speaking, there are two different ways that you might go about deciding what to work on next.
- Idea-driven. Follow some sector of the literature. As you read a paper showing how to do X, you have an idea of how to do X even better. Then you embark on a project to test your idea.
- Goal-driven. Develop a vision of some new AI capabilities you’d like to achieve, and solve problems that bring you closer to that goal. (Below, I give a couple case studies from my own research, including the goal of using reinforcement learning for 3D humanoid locomotion.) In your experimentation, you test a variety of existing methods from the literature, and then you develop your own methods that improve on them.
John links to some other articles on this theme. Richard Hamming, You and your research based off his work at Bell labs, voices some useful ideas on social engineering and genius and effort.
On this matter of drive Edison says, “Genius is 99% perspiration and 1% inspiration.” He may have been exaggerating, but the idea is that solid work, steadily applied, gets you surprisingly far. The steady application of effort with a little bit more work, intelligently applied is what does it. That’s the trouble; drive, misapplied, doesn’t get you anywhere. I’ve often wondered why so many of my good friends at Bell Labs who worked as hard or harder than I did, didn’t have so much to show for it.
The notion of stereotype threat has gotten some press lately; I want to also bring people’s attention to the slightly less-discussed notion of solo-status.
This essay jumps off from Moon Duchin’s on the sexual politics of genius (Duchin 2004).
Michael Nielson, Principles of Effective Research:
People who concentrate mostly on self-development usually make early exits from their research careers. They may be brilliant and knowledgeable, but they fail to realize their responsibility to make a contribution to the wider community. The academic system usually ensures that this failure is recognised, and they consequently have great difficulty getting jobs. Although this is an important problem, in this essay I will focus mostly on the converse problem, the problem of focusing too much on creative research, to the exclusion of self-development.
- If there are already smarter people around, how can I find good ideas?
- Focus Is Saying No To Good Ideas
- Matt Clancy, Age and the Nature of Innovation “Are there some kinds of discoveries that are easier to make when young, and some that are easier to make when older”?
6 Funding
See research funding.
7 Communicate better
8 Strategic ignorance
See strategic ignorance.