Ask HN: Is a Master's Degree in Bioinformatics a Foolish Idea?

Your assessment is correct.

Become a software developer, with a skill set in bioinformatics. Not a bioinformaticians with a skill set in software. It's a tool, not a profession.

I'm not in the field, but a few thoughts...

- If you can code, you don't need the degree.

- If you want professional respect in science, you need the Phd. If it's a quantitative Phd, it can be useful outside of bioinformatics.

- You're more likely to get sponsored for the Phd.

I'm a bioinformatics scientist with an MS.

1) There are a lot of jobs for people with an MS, the hardest part is getting the initial experience though.

2)Pay seems to be all over the place, I make 65k in an expensive city right now. I have had a lot of recruiters contact me with offers that are close to double what I make currently, but they want a couple years of experience first. However, I also see a lot of jobs that require experience that are paying the same or less than what I make now.

3)I don't think there is that much of an oversupply yet, but since a lot of biotechs don't want to pay decent wages and can't get bioinfo. people with what they're offering, they often just grab a bench scientist that has a little bit of coding experience.

4)Yes, there is much less respect from bench scientists and they look at you as a tool to accomplish what they want to accomplish.

Working conditions only seem so bad because of where you are coming from. The conditions are very typical for biotech, if not slightly better (low pay, not a lot of freedom, requires extensive education). I've actually been looking for a good analysis on biotech wages compared to other industries for awhile - so if anyone has one, feel free to pass along.

I came from the bio side, so I got my MS in bioinformatics specifically because it is so interdisciplinary. I doubt I will stay in this industry for the entirety of my working career, likely will move over to health-tech or try my hand at a start-up focusing on services for bioinformatics.

I have a bench biology background. Have looked into bioinformatics as a career option before, but I just went the straight corporate route and got into a finance company as an analyst and then engineer. Just not enough good paying jobs to go around in bioinformatics.

I'm working towards a phd in genomics right now, primarily doing bioinformatics. Here are some thoughts:

1. You're almost certainly likely to make more money doing something else, like web development or finance. Scientists get paid very little money relative to their education and abilities, with the trade-off of interestingness. If you go into it, it shouldn't be for the money. So basically yes in re (2). So for you, doing bioinformatics would probably have to be a goal in your life that you're willing to make sacrifices for.

2. If you want to work on life saving drugs or curing cancer, you could learn how to make some contributions with a MS, but realistically would need a PhD to have more autonomy. Depends on what matters to you.

3. The main benefit would probably be working with a good mentor and helping to decide if you want to go for the PhD. Not sure about your prospects in industry with an MS however.

I'm in science, though not bioinformatics - I know people who are. Cant comment on the oversupply or not, but the positions I know about are primarily funded through short-term grants, which means low-ish pay and minimal job security. I know a few people who have gone the otherway, from bioinformatics to data science.

You might want to look at the career path of this guy:

http://scrippsscholars.ucsd.edu/gsugihara/biocv

Basically, math phd, stint at large finance house, and now works as a researcher essentially self-funding his work.

1. Yes (but applied physics, stats, CS or engineering is more valuable) 2. Yes and no.. if you are not quantitative then yes. 3. Yep quite a few that are more bio than quantitative. 4. This is individual really. Many places have Directors of Bioinformatics. In my experience these people are usually statistically trained or algorithmically trained people. Good at math.

So pick the angle you want. Bioinformatics can be statistics, algorithms, big data, genetics etc...

From a CS perspective, almost everything is a graph and then you have sequences as well. From a stats perspective everything is a noisy data from some model and from a engineering point of view it is signal processing.

Otherwise you are just creating perl/python scripts to munge data into other people's pipelines. That you want to avoid. I think a PhD is really the only way to get around it.

Look at the big tools in the industry and the background of the people who created them.

Lastly you still need a biologist or someone with a bio background to design the experiments and interpret them!!

In regard to 4, probably the best option is to me to be a truly 21st-century biologist that is comfortable both with the bench and computational analysis. But I'm talking about PI level, so a Ph.D is needed.

I had a conversation with some researchers at a major biology/genomics research lab in Maine last week and they pushed back hard when I asked if they were mainly looking to hire PhD candidates. Apparently it's a real problem that grad students and postdocs come onto their projects for just a couple of years and then move on, leading to frankenstein code and unfinished projects that no one can easily pick up and continue. They claim that they would very much like to hire developers who wanted to work long-term on bioinformatics software not just as a means to a PhD.

I did an Msc in Bioinformatics before continuing to a PhD in CS. I'd say that your assessment is largely correct. In general, I'd advise anyone to go into a CS masters. You can always jump to a bioinformatics job without much difficulty, but the opposite move isn't always true. The other replies have also noted that there's a lot of bioinformaticians who are basically scripters. Their jobs consist of running ad-hoc analysis scripts for other people. It's okay but not the most rewarding in terms of job satisfactions, because of point (4) in your post. The other posted who mentioned that the source of funding often comes from short-term grants is also correct in my experience. This means your job tend to be low-paid and last only as long as the grant duration. Altogether I must say, if you're happy in data science stuff, stay where you are. I'm making the move out from bioinformatics as well.