As part of my work for Cognito Mentoring reviewing biomedical research as a career option (not much at the link there right now), I came across an interview with biomedical researcher John Todd of Cambridge University published by 80,000 Hours.

The whole interview is interesting, but one part of it struck me as interesting and somewhat hard to believe:

John would prefer a good person in his lab to an extra £0.5mn in annual funding. Generally, there are enough grants, so finding good people is a bigger constraint than money.

Here's the full context:

Our candidate does data analysis in finance, earning over $100,000 per year. They have an Economics degree for Chicago, and an Masters in Financial Engineering from University of California, LA, and reasonable programming skills. They’re planning to do an MD then PhD.

“This guy looks great. I’d love to hire him.” (when he has his MD, or even before).

“The MD and programming/statistics combo is lethal. Top of the world. There’s major demand.”

He probably wouldn’t need to do a PhD, because of the programming. After his MD, he could just apply to a lab. He should go into genomic medicine, which is what I do. Tailored therapeutics or stratified medicine will be played out for major health and economic benefits over the next 30 years. Check out Atul Butte at Stanford. He’s the perfect profile for this guy. He could be the new Butte”

 

£0.5mn is about USD 830,000 according to current foreign exchange rates. In other words, John Todd, the interviewee, indicated that a sufficiently good researcher was worth that much. Now, the question was framed in terms of additional funding, rather than reallocation of existing funds. But assuming that the existing funding for the biomedical research lab is at least one order of magnitude greater than the amount (£0.5mn) under discussion, I don't think it matters whether we're talking of using additional funding or reallocating existing funds. Essentially, I read John Todd as saying that he'd be willing to pay £0.5mn to attract a "good person" to his lab (actually, as framed, it could be interpreted as even more: he's willing to pay an ordinary salary for the person, plus forgo £0.5mn in additional funds, to hire the person). Note: I clarified with Ben Todd, the interviewer, that the additional grants were per-year rather than one-time grants, so the relevant comparison is indeed between the grant amount and annual income.

I haven't surveyed the biomedical research community, so I'm not sure how representative John Todd's opinion here is. Andrew McMichael offers a more guarded response, suggesting that 200,000 pounds are not as good as a great researcher, but he's less sure at half a million pounds, and in any case, good researchers bring in their own grant money, so it's a false dichotomy. But I've heard that there are other people at biomedical research labs who place even higher value on hiring good people than John Todd does. So in the absence of more detailed information, I'll take John Todd's view as a representative median view of a segment of biomedical research labs.

So, question: why don't there exist high-paid positions of that sort in biomedical research for entry-level people? For comparison, one list of the top ten professors in the US lists the tenth highest paid professor as earning slightly under US$500,000. The list is probably far from complete (Douglas Knight points in the comments to Chicago having at least 5 salaries over $700K, one in the business school and four in the medical school). Glassdoor list salaries at the J. Craig Venter Institute, and the highest listed salary is for professors (about $200,000), with all other salaries near or below $100,000.

I asked a slightly more general version of the question in this blog post. I'll briefly list below the general explanations provided there, with some comments on the applicability of those to the context of biomedical research as I understand it.

1. Talent constraint because of cash constraint: I don't think this applies to biomedical research. It's not that I think they are adequately funded, but rather, they do have enough funds that there shouldn't be a great different between how they would use additional funds and how they would reallocate existing funds.
2. Genuine absence of talented people: I think that this does apply in the very short run -- it's hard for somebody to acquire a M.D. and experience with programming at short notice. But this raises a whole host of questions: why not advertise for such positions prominently, promising high pay, so that people can use the existence of such positions to make more long-term plans of what subjects to study while they're still in college?
3. Talented people would or should be willing to work for low pay: While this argument works well in the context of effective altruism (because of the altruistic orientation needed for top work), I'm not sure it works for biomedical research. I don't see biomedical research as qualitatively different from computer programming or finance in terms of how altruistic people need to be to work productively.
4. Workplace egalitarianism and morale: There may be friction in labs if some people get paid a lot more, particularly if other workers aren't convinced that the people getting paid more are really working harder. This is a problem everywhere, including in the programming world. One solution that the programming world has come up with is to offer different levels of stock compensation. Another solution is acquihires: rather than paying huge salaries to star programmers, companies buy startups that have collected a large number of star programmers under their roof, and the programmers cash in on the huge amount of money reaped through the sale. Neither of these specific solutions works in the context of nonprofit, university, or government research.
5. Irrationality of funders: Employers and their funders are reluctant to pay large amounts. Biomedical research labs are often affiliated with universities and need to use the payscales of the universities. Even those that rely on other donations may be afraid that their donors will balk if they pay huge salaries.

Of course, one possibility is that none of these explanations really matter and I'm overinterpreting offhand remarks that were not intended to be taken literally. But before jumping to that conclusion, I'd like to get a clearer sense of the dynamics at play.

The nature of the explanation could also affect the social value of going into biomedical research in the following sense: if (3), (4), or (5) are big issues, that could be an indicator that perhaps superstars aren't valued much by their peers and funders (relative to the need to make people conform to norms of taking low pay). This suggests (though it doesn't prove) that perhaps the workplace doesn't offer enough flexibility for the sort of ambitious changes that superstars may bring about, so the marginal value of superstars in practice isn't as high as it could be in principle. In other words, if your bosses don't value your work enough in practice to pay you what they say you're worth, maybe they won't give you the autonomy to actually achieve that. On a related note, this GiveWell blog post hints that many experts think that bureaucracy, paperwork, and a bias in favor of older, established scientists, all get in the way of accomplishment for young, talented researchers:

• The existing system favors researchers with strong track records, and is not good at supporting young investigators. This was the most commonly raised concern, and is mentioned in all three of our public interviews.
• The existing system favors a particular brand of research – generally incremental testing of particular hypotheses – and is less suited to supporting research that doesn’t fit into this mold. Research that doesn’t fit into this mold may include:
  • Very high-risk research representing a small chance of a big breakthrough.
  • Research that focuses on developing improved tools and techniques (for example, better microscopy or better genome sequencing), rather than on directly investigating particular hypotheses.
  • “Translational research” aiming to improve the transition between basic scientific discoveries and clinical applications, and not focused on traditionally “academic” topics (for example, research focusing on predicting drug toxicity).
• The existing system focuses on time-consuming, paperwork-heavy grant applications for individual investigators; more attention to differently structured grants and grant applications would be welcome. These could include mechanisms focused on providing small amounts of funding, along with feedback on ideas, quickly and with minimal paperwork, as well as mechanisms focused on supporting larger-scale projects that require collaboration between multiple investigators.

I wrote this post up and circulated it among my rationalist friends. I've copied it verbatim. I figure the more rationally inclined people that can critique my plan the better.

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TL;DR:

* I'm going to commit to biomedical engineering for a very specific set of reasons related to career flexibility and intrinsic interest.
* I still want to have computer science and design arts skills, but biomedical engineering seems like a better university investment.
* I would like to have my cake and eat it too by doing biomedical engineering, while practicing computer science and design on the side.
* There are potential tradeoffs, weaknesses and assumptions in this decision that are relevant and possibly critical. This includes time management, ease of learning, development of problem solving solving abilities and working conditions.

I am posting this here because everyone is pretty clever and likes decisions. I am looking for feedback on my reasoning and the facts in my assumptions so that I can do what's best. This was me mostly thinking out loud, and given the timeframe I'm on I couldn't learn and apply any real formal method other than just thinking it through. So it's long, but I hope that everyone can benefit by me putting this here.

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So currently I'm weighing going into biomedical engineering as my major over a major in computer science, or the [human-computer interaction/media studies/gaming/ industrial design grab bag] major, at Simon Fraser University. Other than the fact that engineering biology is so damn cool, the relevant decision factors include reasons like:

1. medical science is booming with opportunities at all levels in the system, meaning that there might be a lot of financial opportunity in more exploratory economies like in SV;
2. the interdisciplinary nature of biomedical engineering means that I have skills with greater transferability as well as insight into a wide range of technologies and processes instead of a narrow few;
3. aside from molecular biology, biomedical engineering is the field that appears closest to cognitive enhancement and making cyborgs for a living;
4. compared to most kinds of engineering, it is more easy to self-teach computer science and other forms of digital value-making (web design or graphical modelling) due to the availability of educational resources; the approaching-free cost of computing power; established communities based around development; and clear measurements of feedback. By contrast, biomedical engineering may require labs to be educated on biological principles, which are increasingly available but scarce for hobbyists; basic science textbooks are strongly variant in quality; and there isn't the equivalent of a Github for biology making non-school collaborative learning difficult.

The two implications here are that even if I am still interested in computer science, which I am, and although biomedical engineering is less upwind than programming and math, it makes more sense to blow a lot of money on a more specialized education to get domain knowledge while doing computer science on the side, than to spend money on an option whose potential cost is so low because of self study. This conjecture, and the assumptions therein, is critical to my strategy.

So the best option combination that I figure that I should take is this:

1. To get the value from Biomedical Engineering, I will do the biomedical engineering curriculum formally at SFU for the rest of my time there as my main focus.
2. To get the value from computer science, I will make like a hacker and educate myself with available textbooks and look for working gigs in my spare time.
3. To get the value from the media and design major, I will talk to the faculty directly about what I can do to take their courses on human computer interaction and industrial design, and otherwise be mentored. As a result I could seize all the real interesting knowledge while ignoring the crap.

Tradeoffs exist, of course. These are a few that I can think of:

• I don't expect to be making as much as an entry level biomedical engineer as I would as a programmer in Silicon Valley, if that was ever possible; nor do I believe that my income would grow at the same rate. As a counterpoint, my range of potential competencies will be greater than the typical programmer, due to an exposure to physical, chemical, and biological systems, their experimentation, and product development. I feel that this greater flexibility could help with companies or startups that are oriented towards health or technological forecasting, but this is just a guess. In any case that makes me feel more comfortable, having that broader knowledge, but one could argue that programming being so popular and upwind makes it the more stable choice anyway. Don't know.
• It's difficult to make money as an undergraduate with any of the skills I would pick up in biomedical engineering for at least a few years. This is important to me because I want to have more-than-minimum wages jobs as a way of completing my education on a debit. While web and graphic designers can start forming their own employment almost immediately, and while programmers can walk into a business or a bank and hustle; doing so with physics, chemistry or biology seems a bit more difficult. This is somewhat countered by co-op and work placement, and the fact that it doesn't seem to take too much programming or web design theory and practice before being able to start selling your skills (i.e. on the order of months).
• Biomedical Engineering has few aesthetic and artistic aspects, the two of which I value. This is what attracted me to the media and design program in the first place. Instead I get to work with technologies which I know will have measurable and practical use, improving the quality of life for the sick and dying. Expressing myself with art and more free-wheeling design is not super urgent, so I'm willing to make this trade. I still hope to be able to orient myself for developing beautiful and useful data visualizations in practical applications, like this guy, and to experiment with maker hacking.

There is still the issue of assuring more-than-dilettante expertise in computer science and design stuff (see Expert Beginner syndrome: http://www.daedtech.com/how-developers-stop-learning-rise-of-the-expert-beginner). I am semi-confident in my ability to network myself into mentorships with members of faculty [at SFU] that are not my own, and if I'm not good at it now I still believe that it's possible. In addition, my dad has recently become a software consultant and is willing to apprentice me, giving a direct education about software engineering (although not necessarily a good one, at least it's somewhat real).

There are potential weaknesses in my analysis and strategy.

• The time investment in the biomedical engineering faculty as SFU is very high. The requirements are similar to those of being a grad student, complete with a 3.00 minimum GPA and research project. The faculty does everything in its power to allay the burden while still maintaining the standard. However, this crowding out of time reduces the amount of potential time spent learning computer science. This makes the probability of efficient self-teaching go down. (that GPA standard might lead to scholarship access which is good, but more of an externality in this case.)
• While we're on the conscientiousness load: conscientiousness is considered to be an invariant personality trait, but I'm not buying it. The typical person may experience on average no change in their conscientiousness, but typical people don't commit to interventions that affect the workload they can take on either by strengthening willpower, increasing energy, changing thought patterns (see "The Motivation Hacker") or improving organization through external aids. Still, my baseline level of conscientiousness has historically been quite low. This raises the up front cost of learning novel material I'm not familiar with, unlike computing, of which I have a stronger familiarity due to lifelong exposure; this lets me cruise by in computing courses but not necessarily ace them. Nevertheless, that's a lower downside risk.
• Although medical problems are interesting and I have a lot of intrinsic interest in the domain knowledge, there are components of research that interest me while others that I don't currently enjoy as much as evidenced from my current exposure. I can seem myself getting into the data processing and visualization, drafting ergonomic wearable tech, and circuit design especially wrt EEGs. Brute force labwork would be less engaging and takes more out of me, despite systems biology principles being tough but engaging. So there's the possibility that I would only enjoy a limited scope of biomedical engineering work, making the major not worth it or unpleasant.
• Due to the less steep learning curve and more coherent structure of the computer science field, it seems easier to approach the "career satisfaction" or "work passion" threshold with CS than for BME. Feeling satisfied with your career depends on many factors, but Cal Newport argues that the largest factor is essentially mastery, which leads to involvement. Mastery seems more difficult to guage with the noisy and prolonged feedback of the engineering sciences, so the motivations with the greatest relative importance might be the satisfaction of turning out product, satisfying factual curiosity or curiosity about established/canon models (as opposed to curiosity which is more local to your own circumstances or you figuring things out), and in the case of biomed, saving lives by design. With mathematics and programming the problem space is such that you can do math and programming for their own sakes.
• Most instances of biomedical engineering majors around the world are mainly graduate studies. The most often reported experience is that when you have someone getting a PhD in biomedical engineering, it's in addition to their undergraduate experience as a mechanical engineer, an electrical engineer or a computer scientist. The story goes that these problem solving skills are applied to the biology after being developed - once again a case of some fields being more upwind than others. By contrast, an undergradute in bioengineering would be taking courses where they are not developing these skills, as our current understanding of biology is not strongly predictive. After talking to one of the faculty heads, the person who designed the program, he is very much aware of problems such as these in engineers as they are currently educated. This includes overdoing specialization and under-emphasizing the entire product development process, or a principle of "first, do no harm". He has been working on the curriculum for thirty years as opposed to the seven years of cases like MIT - I consider this moderate evidence that I will not be missing out on the necessary mental toolkit over other engineers.
• In the case where biomedical engineering is less flexible than I believed, I would essentially have a "jack of all trades" education meaning engineering firms in general would pass over me in favor of a more specialized candidate. This is partially hedged against by learning the computer science as an "out", but in the end it points to the possibility that the way I'm perceiving this major's value is incorrect.

So for this "have cake and eat it to" plan to work there are a larger string of case exceptions in the biomedical option than the computing options, and definitely the media and design option. The reward would be that the larger amount of domain specific knowledge in a field that has held my curiosity for several years now, while hitting on. I would also be playing to one of SFU's comparative advantages: the quality of the biomedical faculty here is high relative to other institutions if the exceptions hold, and potentially the relative quality of the computer science and design faculties as well. (This could be an argument for switching institutions if those two skillsets are a "better fit". However, my intuition is that the cost for such is very high and probably wouldn't be worth it.)

Possible points of investigation:

• What is hooking me most strongly to biomedical engineering were the potentials of cognitive enhancement research and molecular design (like what they have going on at the bio-nano group at Autodesk: http://www.autodeskresearch.com/groups/nano). If these were the careers I was optimizing towards as an ends, it might make more sense to actual model what skills and people will actually be needed to develop these technologies and take advantage of them. After writing this I feel less strongly about these exact fields or careers. Industry research still seems like a good exercise.
• I will have to be honest that after my experience doing lab work for chemistry at school, I was frustrated by how exhausted I am at the end of each session, physically and mentally. This doesn't necessarily reflect on how all lab work will be, especially if it's more intimately tied with something else I want to achieve. And granted, the labs are three hours long of standing. It does make me question how I would be like in this work environment, however, and that is worth collecting more information for.
• To get actual evidence of flexibility in skillset it would be worth polling actual alumni from the program, to see if any of the convictions about the program are true.

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Thoughts, anyone?

I'm a high school senior from Europe and in a few months I'll be heading to university.

I have a keen interest in the human body. As such, I would like to work in emerging interdisciplinary fields, such as stem cell transplantation and suspended animation.

I could go on to study, say, Biomedical Science, but I'm also fascinated with Engineering. That is, I think that my aspirations, which are to improve human condition, could be well served from an Engineering standpoint.

What do you think? Would my interest in the human body and its applications be better suited for Engineering or for Biomedical Science? How should I decide what to study?