Industry: 60-70 + + research skills + publications+ inter personal skills + city where you work. In industry they might have research or service. service tends to be on low side. research - where investigator has money and you are working for him

PhD in bioinformatics Academia:
This is all together a different equation:
equation a: If you do not have research plan and want to work in a core
estimate could be (55-60)+ research skills + publications+ inter personal skills + city where you work.

equation b: If you have a research plan and take a ‘track’ position,
60-65 + research skills + publications+ inter personal skills + city where you work

Industry:

This is more of a bargain game. You are talented, and you have publications to demonstrate your ability, you bet for more.
More can be 120-130 K depending on location.
In S. san francisco (big leagues ‘G’ or ‘AM’) - notorously low paying biotech jobs with extra perks You can be happy with ‘G’ shares and stocks. Also at ‘G’ you enjoy camrederie of big league scientists and feel like working at Caltech or standord.

In seattle - I would also say the same may be 110-120 could be more appropriate.

Hope this helps to get more insight on how things are.

Best wishes,

Sheila

As stated, I’m currently working in academia and the salary in academia is lower than the private/industry - after all the motivation is discovery and not money. If you’re just starting (0-2yrs of experience) it’s unlikely you’ll get paid $70K (I’m not sure which job pays that high without even an undergrad degree). I’ll be also surprised to find any internship in Bioinformatics that pays >$40K. Case in point, most post docs (in academia) get paid around that amount and it’s unlikely an intern or a temp would get paid high. But again, this is just for Bioinformatics, if you’re looking for a job as a software engineer in Bioinformatics things will be different…

I read pretty much all the posts, and probably two people posted the actual figures of how much a Bioinformatician could earn. Most shocking of all was the last post from “Ske”. Even though you have a MS in Bioinformatics you’d earn between $40K - $50K? That I reckon is really under paid. An intern completing his CPT/OPT in an IT industry could earn $40K/yr easily…correct me if I’m wrong. You don’t even need an undergraduate degree to be earning close to $70k, if you’re good at programming. So, why is the job market so cheap for Bioinformaticians?

@Morgan
I would say that in academia, certainly in the UK and US, I got the impression that if you’re not publishing enough, and pulling in grants, your position is somewhat in jeopardy. Industry on the other hand seems to offer the protection of a large company, and as long as you pull your weight, you’re secure. Of course, your job will be subject to the whims of the market, which could mean you lose your it because the company doesn’t do so well.
Anyway, this is my opinion, and I’m still a student as yet to make the choice between the two.

@Under caffeinated
I never mentioned crusty. In science I don’t think you need to be old to get a fair amount of crustiness either.
I couldn’t agree more about numerate skills. Statistics and data mining are certainly in demand. From my point of view though, I wasn’t interested in learning any of this during my masters - after all statistics comes across as a very dry subject. It was only when I had a lot of data that I felt the need to reeducate myself on the subject. I guess this could be the case for a lot of the more important skills?

I can’t really give you any advice on what career path you should take, I’m only a PhD student also. Ask me when I have graduated and found a job perhaps? You could discuss these worries with your supervisor, or other professors in your department. Try posting the same question on Nodalpoint.org too.

An interest in biology is always useful, as is programming. I would say that advanced programming skills are only useful if you’re building an application, otherwise a lot of the work involves building simple scripts to process the data - which doesn’t require to much know how. I used to use Java, but now I use Ruby. I would recommend Ruby or Python as they seem to be becoming more prominent in Bioinformatics, for me Ruby is also a pleasure to write.

As for studying metabolomics, or any other field, I think most of your knowledge will come from the literature. Reading plenty of papers at the start of your PhD is always a very good idea, as this help you understand the problem better as well as make you feel more confident. when discussing things with colleagues.

I am newbie to PhD and quite passionate in knowing biology stuff. However, I came from Comp Science background. I am planning to move into bioinfo area. However, I am doubtful with the amount of tedious work than other computer science area which would not have steeper learning curve.

Besides, as mentioned above, it is hard to find a job for bioinformatics upon coming out. Most companies would not want to employ employee with area whihc unrelated to their business needs.

And besides, I am kinda doubtful as my programming is not really good. Should I be qualified to take the path of bioinformatics.

Please advise.

-Jason

While most ‘working bioinformaticians’ that I come across have one of the two traditional backgrounds, the increasing use of mathematics and statistics in biological data analysis has made the field attractive to numerate physics and mathematics PhD graduates. I can only speak from my own vantage point, but I’d recommend any MSc in Bioinformatics student to consume as much statistics as is practically possible during their course, even if it means reading outside the course syllabus. It will make you more competitive in a head-to-head comparison with these guys by potential employers.

I’d be so bold as to venture that in the not too distant future bioinformaticians without a numerate grounding will find themselves working with data management and pipelines (which can be very mundane, believe me), and those with numeracy/statistics skills will be doing the jucier downstream bioinformatic analysis.

Also, it is interesting how everyone has their own definition for computational biologists vs. bioinformaticists. I actually call computational biologists those people that develop primarily algorithms (i.e. computer scientists that work on biology problems). I then tend to group those people who seek to develop tools and those people who answer biology questions together into bioinformatics.

Anyway, I really enjoyed your post. I am also in that twilight of picking industry vs academia.

@Adouble
I accept your point, here in the UK I think it would difficult to get a six figure salary, while in America I think industry and academia is much more highly paid, compared with, say, Europe. I think that this is something worth considering, if you move to America, you may be paid relatively more.

@laser
I’ve heard this too. I’ve been told that if you don’t have a PhD there is only so far you can get before you have to move into an administrative position, or hit some sort of ceiling.

@Animesh
I based my statement on the numbers working in my department now, as well as the numbers in my master’s degree. I did not mean to cast aspersions. Certainly, quantitative research is very important, take for example the rapid rise of systems biology; which owes a lot to Mathematics and Physics. I completely agree that a numerical approach is where the greatest breakthroughs in biology will be made. Take this paper for example.

Second point … if I had to make the choice all over again, I’d choose industry over academia even more easily. I think academia can get more bogged down than industry. But in the end it’s about your particular mental make up. Here are some of the reasons I like my choice of industry

1. You work in cross disciplinary teams
2. You get a really good understanding of many aspects of drug development, even if you are not directly involved
3. In smaller startups, you tend to have a sense of ownership that is very satisfying
4. There can be a lot of pressure - to meet deadlines, to turn things around quickly. Some people thrive on that
5. You have the option, not always available, to move onto the business end of things like I did

The key part is realizing that you are working on someone else’s time, but many times you are also contributing to something very exciting and potentially difference making (depends on where you are)

Last point. You are right about the salaries. In the end it’s your skill and experience level, but you do end up earning a six figure salary in due time, just not when you get started, but that won’t be happening in most jobs in any field. My only beef is that the PhD does not get sufficient respect as a degree, compared to say an MBA.