Hey Blashimov,

I don't even know if you are still paying attention to LW, but I just found this response. Yes, there is some semblance of a LW group in Houston, mostly focused around the Rice/Med center area, unsurprisingly. Right now, we're on temporary hiatus. There are three regular members, including myself. We have been going over ET Jayne's "The Logic of Science", but our collective workloads have gone up recently, and we were no longer able to put in the effort required to get something out of it. Hopefully we will get started back again in the summer when we all have more time.

It also looks like there will be a club focused on the singularity and surrounding issues at Rice soon. There are a dozen or so people interested in learning neural networks, computational biology/neuroscience, bayesian stat, etc. I plan to help with that a lot, and it's a good possibility that a Houston LW group might be tightly integrated with that group. One of our problems was lack of people, and this would be a good pool to draw from. I'll send you more information about it if you want.

I recall seeing opposite advice regarding extraverts and introverts on some TV show about dinner parties a long time ago. They suggested alternating them when arranging a table - the extroverts should be close enough to talk, but they have to talk around introverts. Introverts would have the opportunity to fluidly join conversations going on around them and have an easier time disengaging because someone else beside them will fill in the gap. Obviously, this would be miserable for an extreme introverts, but you can put those people in a corner.

Again, this is a half remembered piece of information, but it stuck with me because it seems to make sense.

One additional point - I think it has been made above, but it is good to emphasize: If you want to do any biological science at a high level, focus on hard subjects in undergrad. It's still difficult to learn organic chem or neuroanatomy in grad school, but it's much more difficult to add mathematical skills to your repertoire if you're doing time consuming wet lab work in grad school. Mathematics/Engineering/Physics will get you into better schools, and bio programs will be happy to have you. Every time I talked to a professor, they became much more interested me when they learned of my physics background.

My own history is majoring in physics, psychology, and philosophy. Neuroscience fell out of that for me. If you really want neuroscience, and a head start will really help with a career, then I would suggest a similar undergrad course - some hard field paired with psychology or neuroscience. Make friends with a professor in the softer field, and do lab work there. That will look good on the resume, and it will let you know if you actually like the day to day work. The softer field also helps with point 8 below, which I wish I knew earlier in college.

I am currently in my second year as a grad student, focusing in theoretical/computational neuroscience. Here are my observations on the matter:

1) Neuroscience is a hard science, but as in many things, there’s a continuum. The computational folk are at the hardest part, while the fMRI researchers are considered the softest. In general, the larger the structure you study, the softer it is. Exceptions exist, and within the field there are controversies as to how solid some of the theoretical frameworks are for even the most rigorous parts of the profession.

2) My own observations on average time spent on the job is about 50 hours a week, with some fairly extreme flexibility. Almost all my work is reading and programming, so most days I don’t have to I don’t even have to come in (I do, but that’s because I’m more productive in an office). People on the biology side of things do not have quite that flexibility. If you take human subjects, particularly hospital patients instead of college students, then your life will revolve around them.

3) My program has no requirement to TA, which is a huge time suck. I’m unsure how prevalent TAing is in neuroscience. My general impression is that the better your program, the less likely you are to have to do it. Similarly, if you go to a primarily graduate university, you will spend less time teaching. If you can find a program that lets you avoid that, then do so. Being a TA seems to be the leading cause of misery in grad school.

4) Currently, my pay is $29K/year as a grad student, and post doc pay tends to be in the $40Ks. Full professorship pay (at least in computational) is >80K. As to how likely a full professorship is, see my comments on job prospects. Obviously, location is going to make a difference. My stipend means I live very well in Houston. If I studied at NYU, which has a comparable stipend, I would effectively be much poorer.

5) If all you want is $40K/year, then you’ll be fine. You can be an eternal post-doc and manage that. That being said, I suspect you will revise your estimates up. It can be really hard to see your friends getting other professional degrees with the same or less work and raking in substantially more than you. It’s also hard knowing that you can quit at any time and make substantially more money within a year or two of education. As much as it sucks, knowing about opportunity costs can really dampen your enjoyment of life. You have to resist that, but it takes effort. To keep up with the engineering/M.D./business Joneses, you have to advance in the ranks.

6) High level job prospects in academia: Yeah, you know this isn’t great. Neuroscience fairs better than most sciences because there is so much low hanging fruit, but still, you’re facing an uphill battle. You have to be fully willing to move around until your 40s, possibly to other countries. Many signs point to a decrease in governmental funding and an increase in competition. Business is not picking up the slack. Tenure is going away. I’m aiming for this, and my heavy computational focus has better odds than most, but I have backup plans.

7) High level job prospects outside academia: Better than academia, but depends a lot on how fast the field progresses. You’ll reach your prime around 15 years from now. Neural prosthetics might (that’s a big might) come online by that time and be a big industry. Some types of neural enhancements will hit the market within 30 years, so it could be very profitable if you position yourself right. Integrated computer chips based on neural architectures are beginning to be mass-produced now, so knowledge of existing and highly functional architectures (brains) might make you very valuable. You will become very knowledgeable about people, decision making, and modeling if you do the theoretical branch, so I don’t see much difficulty spinning that into business and stock consulting, especially if grab an MBA. Medical equipment design is always lucrative. Medical consulting is a possibility. Also, the better the industry outside of academia, the easier academia gets (more funding/ less competition)

8) Neuroscience is cool. Don’t underestimate how nice it is to have people want to talk to you about your subject of study. Being an engineer, mathematician, physicist, etc. can really suck sometimes. Subjects like that are really difficult if not impossible to get people interested in. I mention neuroscience in passing, and a huge number of people are interested in what I do. You do have to put up with stupid comments (“What if like your brain is a particle and a wave and collapses the universe, man?”), but I’ve done physics. Socially, dealing with stupidity is easier than obscurity. Economics might be similar, but because of its relationship to politics, it breaches the mindkiller zone and I suspect it would be much less fun to talk about.

I'll answer any other specific questions you might have too.

[Edited for clarity]

I have been told that math would also help in English and other humanities as well. Statistical analyses of literature, as well as things like procedurally generated narratives, are beginning to take root. Literary/artistic criticism through the lens of neuroscience/cognitive psychology is also ready to take off, so many of the scientific fields listed above would be useful.

This is not to say that I think that a focus in humanities will lead to the greatest personal utility, but if you feel that you must do something in that vein for a career, then a background in hard science/math would be a good thing. It will make you quite unique and valuable, something that you will need if you enter that horribly over saturated market.