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Career Choices for Computational Biologists?
wengkius writes "I'm entering grad school this year and will be working towards a higher degree in Computational Biology. While my undergraduate training has been in computer science, I'm looking to apply what I've learned in a new area that has piqued my interest. Now my question is this: apart from the obvious career choices that I have thought of (academic research, pharma corporations, biotech startups), are there any other career options that I have yet to consider? Would be great to hear from Slashdotters who are familiar with the field."
Huh? Sorry, IANAL nor a degreed professional, but if I'd spent that much time of my life and that much money... uhm, I'd have given it way more thought than you seem to have done.
/.'s opinion of the worth of computational biology, well I'd say that there is lots of work to be done yet. That whole genetic splicing and stem cell research and genomic research etc. There is also AI and robotics research teams that you might find interesting.
Not to slam you unconditionally, I'm sure you have given this some thought, but since we don't really know what you are good at and what you like (other than school) how about you give us a multiple choice list of things you have considered and we as slashdotters will duly vote in the latest poll.
If you simply want
I'll wait for the multiple guess poll, thanks.
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Plastics.
My advice -- be familiar with the tools and techniques, and pick a fun and collaborative project. Whether computational chemistry (my field) or biology, the tools that you use can and will be applied elsewhere. Being familiar with measures of similarity (Tanimoto similarity, for instance), has implications to multiple fields, as does multivariate modeling (PLS, SVMs, K-nearest-neighbor models, etc). I know several grads who 'jumped ship' to market analysis/market prediction (think brokerages and Wall Street). The point is, you become an expert in your field, and have the offers come to you.
Cheers,
-Mike
If a man's character is to be abused there's nobody like a relative to do the business. -Thackeray, William
Two words.
Biotech startups.
In the question for fucks sake.
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It depends on your program's definition of Computational Biology. Traditionally, Computational Biology and Bioinformatics have referred to the same general type of work, but more recently each has taken on more precise meanings, especially in industry. Computational Biology primarily refers to ab-initio, in-silico modeling of biological systems (conformation, docking, systems biology simulations). Bioinformatics refers to the analysis of biological data, primarily from the various "omics" (genomics, proteomics, transcriptomics, etc).
In industry, computational biology is viewed with a healthy dose of skepticism. The promise of in-silico modeling has been just around the corner since the 70s and no system has yet delivered on the promise. If this is what you're doing, stay in academia and keep working on the dream (but, apply to D.E. Shaw Research on the off chance you can get a job there, they're building a supercomputer for this). Or, if you would like a bigger paycheck and more predictable work, switch over to computational chemistry, which is much more accepted and an important component of most drug discovery pipelines.
Bioinformatics, on the other hand, is basis of many product and research groups. The most important skills are the ability to communicate with biologists and experience with genomic databases, genomic search tools, and statistical modeling along with the ability to tie it all together programatically. This often includes developing data mining pipelines and creating nice Web interfaces for the scientists to access them with. Good CS and programming skills can give you a leg up over the people with bioinformatics degrees. If this is what you want to do and you're young/single, biotech startups or bioinformatics startups are a lot of fun. You'll work hard and the company will probably go under, but it's a great way to get deep experience in the field and make connections for your next job.
Right now, the most exciting industrial work is probably around next-gen sequencing platforms. Look at 454/Roche, Applied Biosystems (SOLiD), or Illumina. Lots of really interesting high-performance computing, algorithmic, and scientific challenges.
Good luck!
-Chris
I work in a computational biology department at a research institution. Everyone I know is either in academic or government research. My only degrees are in Computer Science... I get the biology knowledge I need from my collaborators. Maybe I don't understand your question? What are you hoping to hear? If you are planning on studying for a higher degree in computational biology, that pretty much limits your career choice to "computer scientist working with biology or medical researchers". You are likely to find a job wherever one finds biology and medical researchers (as you noted, academic/government research institutions, biotechs, and pharmaceutical companies). To get a sampling of what jobs in the field look like and what sorts of companies/institutions hire such people, try the International Society for Computational Biology and look at their jobs section.
I would look at your question two ways - are you asking for who to work for, or what to work on? There are a lot of things to do, either way.
In terms of who, your choices are plenty. There are a few general options, which vary depending on the field. In general, you have big fish, small (usually new startup) companies, and of course academia. Each has their pluses and minuses, and you'll probably think differently of each of them by the time you're done in graduate school. I'm on my third year of my biochemistry PhD and I know my opinions on each of them change a lot.
As for what field to go in to - obviously you need to find something you want to do, or you'll end up wanting to shoot yourself. That said, I would also recommend looking into the trends - both in funding and in people. Bioinformatics and genomics were both very popular a few years back, and now a lot of people are graduating with degrees in each. There is plenty of work to be done in those fields, but the competition is getting tougher in funding and job hunting. Other 'omices are getting big - proteomics is a great example - and are seeing the same funding / staffing trend that was observed in bioinformatics / genomics a few years back. I was just at a proteomics conference myself a couple weeks ago, and the head-hunting was astounding.
That said, a wise man once pointed out that you'll find the excitement, funding, and staffing for a new technology to be respectively out of phase - at least until the technology du jour is considered "accepted" and "stable". Computational biology and all of its facets is really interesting, but it can be bumpy at times too. So choose your path wisely.
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..biologists used to get a job working at the local garden centre. Those cabbages need keeping free of slugs. And if you have computational biology, you'll be able to work out the right dose of weedkiller and fertiliser.
Stick Men
I work next to a lab of computational biologists (immunology, actually), and one career path that isn't quite so unusual is finance. There's a lot of demand for excellent quantitative and computational skills in finance/investment banking. It may not be related to biology, but it's a very real possibility.
A program at my previous college would graduate 5-6 bioinformaticians with PhDs a year. The ones who got snapped up were the ones who also had a substantial background in the biology they were working with. Take whatever genetic/bio courses you can fit in along with your bioinformatics work. When choosing a doctoral project, try to find one that involves collaboration between your advisor and professor in the genetics or cell biology department. As some posted above, bioinformaticians can find jobs pretty much anywhere biologists are employed, but the biologists will be important in making any hiring decisions and they want someone who understands the biology in addition to being a wiz at the computational stuff.
Working at a national laboratory is another option. I was an intern at Los Alamos for two summers working on proteomics research as a code monkey. There is a pretty broad array of topics you can work on at places of that size, so that may provide you more opportunity to find something you like than working at a university. And it probably pays better :)
I know it is still academic research, but it is a very different environment than a school lab.
Additionally, knowing what one would want to go into after grad school is essential for making choices about grad school. It's not like he's considering going for a generic "PhD, good for all things that a PhD is good for."
I am an academic, so I only know academia and a little biotech, but I do know that if you have a good background in computers and a good background in biology, you will be able to find lots great jobs for the next 10 years at least in academia or in biotech.
Genomics or protein biochemistry are probably the best fields to head toward.
Genomics will be more skewed toward academia I would think, but there would be a job for you at monsanto if you were interested in corn genomes. Nonetheless, research into genomes is all computer driven and in constant need of people who are more computer minded, and is of course very important.
Protein folding would get you a very good job at any major academic institution and would probably get you a really high paying job at any pharmecutical.
If you're equally interested in both, I would say go toward protein folding, as you're going to be able to find a good post-doc in more places and/or get hired immediately by a pharmecutical for lots of bling.
I wouldn't think that biotech startups would be as a general rule as good to shoot for right after grad school, but that really depends on the startup. It just seems to me that an established pharmecutical giant would be a sure thing, and you would have more funding.
I got my PhD last year in a similar field, and I made the leap into video game development. Best decision I ever made. Besides the fun factor, the biggest issue in a science career (well, in academia at least), is just how freakin long it takes to get your career going. After grad school, 6 years in my case, you have to do a post-doc for a few years, then get (hopefully) get a tenure-track faculty position, then work your ass off to actually get tenure. Then, if everything goes right, your career starts. For me, that time commitment was simply not worth it.
I'm currently a student in a graduate-level biology program. We had a speaker from the USPTO (United States Patent and Trade Office) come and talk to us about a month ago. From what he was saying, the USPTO is dying to recruit more computational biologists. Basically, there's a lot of companies who are trying to patent biological database algorithms, and very few people at the trade office have enough know-how to properly determine if the patent should be granted or not, (or even if such algorithms are even patentable at all).
So, if you don't mind the paperwork and the lack of lab access, then there's a career that will accept you right away (according to the speaker).
"Operating systems suck: you're better off using only the BIOS" --trainsaw.com
I'm just kidding... actually they're giving preference to people with nuclear and quantum physics degrees...
please excuse my apathy
Getting a job through somebody you know from a previous job happens all the time. Maybe it didn't work for you, but it's quite common. I have seen it over and over again and experienced it personally.
Submitter here. Thanks for all those replies. Some of them were really helpful and will no doubt be food for thought when I consider my options. I did an internship in one of the big pharma companies (**K) and managed to do some interesting (to me at least) work related to molecular drug discovery using computational approaches. As a CS student, I would have never imagined using the stuff that I learned on a field such as this. The only thing that gives me reservations about working for big pharma is of course the ethics. I don't mean the animal testing part (security was quite tight at our research site as we were frequently the target of militant animal rights groups) but rather the gouging patients with ridiculously priced drugs part.