

Career Choices for Computational Biologists? 60
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."
1 Word (Score:1, Redundant)
Re:1 Word (Score:4, Funny)
Biotech startups.
In the question for fucks sake.
Translation (Score:1, Funny)
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Get a good education (Score:1, Interesting)
Here's the truth: if you get a really good education then what you are doing 5 or ten years later can be entirely different. So focus on the education not on specific mad skilz. Do learn a new skill at each job however as that's what's going to get you the next job.
Personally, I've published papers in atomic physics, remote sensing, computational biology, medical imaging, information theory and half a dozen other fields, radically changing fields every 5 or ten years. The only
About to graduate? (Score:4, 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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Re:About to graduate? (Score:4, Insightful)
One word... (Score:4, Funny)
Data Mining / Informatics... (Score:4, Informative)
Cheers,
-Mike
Faculty advisor maybe? (Score:1)
We don't know you. He/she does...at least more than us.
Granted, they may be apt to nudge you towards academia, but they should also be very familiar wit
NIH (Score:1, Informative)
You can also check out the Occupational Outlook Handbook (http://www.bls.gov/OCO/) provided by the US Dept. of Labor. You can look around their site, altho' it's not very easy to find exactly what you're looking for.
But I have to wonder, have you talked to any of your professors? What abo
Ask Your Profs (Score:1)
Computational biology, thou
Depends on definition... (Score:5, Insightful)
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
Making connections (Score:1)
I have deep experience in fingerprint analysis, and made connections, but no jobs. I know of others in the same predicament. Experience seems to correlate negatively.
Same for the oil business, and unix system administration.
I now consider it to by a myth that one can get jobs by connections like that.
The reality is getting very different jobs sequentially, as one gets good at a business, and then gets unpopular in that business.
Kim0
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I'd like to second the parent posters remarks. I'm currently contracting in the biomedical informatics department in the research foundation of a large mid-western paediatric hospital.
The fields of study here are wide and varied. They include Semantic Web, Natural Language Processing, Massive Parallel Processing, Data Warehousing and more.
The key things I'd suggest is to get great in one of the following areas: Computational, Statistical or Biological. Then get good in one of the others (hint: Statisti
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Quite simply put, do this. You probably would have more luck winning the lottery (literally), but it's worth a shot. Take a look. [deshawresearch.com] If you haven't heard of D.E. Shaw [deshaw.com] before, they're a hedge fund founded by former computer science professor David Shaw [wikipedia.org] and are universally respected as one of the best hedge funds around.
A bit premature (Score:2)
More than one way to employment (Score:2)
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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 biochemist
What Are You Looking For? (Score:2, Informative)
While you're at it (Score:2)
Question (Score:2)
My impression of graduate study was to prepare you to complete independent/collaborative research, but that may be different for people outside of biology/chemistry etc., such as fields like cs, ce.
Coming from more of
As someone who played the bioinformatics game... (Score:3, Insightful)
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.
In my day... (Score:3, Funny)
..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.
NORBAC (Score:2)
Finance (Score:2, Interesting)
Whale Biologist (Score:2)
Learn to Talk With Biologists (Score:5, Insightful)
Working for the government... (Score:3, Interesting)
Folding at Home? (Score:2)
Video games (Score:4, Interesting)
I hope you just worded that wrong (Score:2)
You need to find out fast whether you really want to specialize in computational biology, whether you're interested in scientific modeling in general, or if you really want to just go make money predic
USPTO (Score:3, Interesting)
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).
Mac Donalds is hiring.... (Score:3, Funny)
Some starting points (Score:2)
Overview of the field:
http://bioinformatics.sdsu.edu/education.htm [sdsu.edu]
News:
http://news.thinkgene.com/ [thinkgene.com]
http://www.bioinformatics.org/ [bioinformatics.org]
Org:
http://www.iscb.org/ [iscb.org]
I assume you've crawled through Wikipedia already -- they break it down pretty well. Also, remember that a startup can be anything, not just a specific kind of work like you've seen in school. It's common in the biotech industry to make your career out of a string of startups; you'll get a pike of options from e
Software (Score:2)
Opportunities are many: keep mind and ears open (Score:1, Informative)
Computational biologists... (Score:2)
Ack! Put down that microtome!
Cancer genomics (Score:1)
Additionally, the new sequencing technologies (for RNA and DNA) are making microarrays obsolete to some researchers, but the increase in data presents a new challenge.
These areas seem a l
Thanks for the feedback (Score:4, Interesting)
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I'm glad your ethical issue has never occurred to me, ridiculously priced drugs gouge the National Health Service (i.e. taxpayer) here, which is at least fairer, even though it still isn't very nice.
Most of my friends -- in fact, most of my class -- have gone to work at investment banks or software companies, generally
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I'm glad your ethical issue has never occurred to me, ridiculously priced drugs gouge the National Health Service (i.e. taxpayer) here, which is at least fairer, even though it still isn't very nice.
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unemployment or unemployment (Score:2)
Software development (Score:2)