Bioinformatics Software Engineering Specific Skill Improvement Advice For New Grad. Level Work

Question

[wid2231auu1]

Hello all,

I graduated with a master's in biomedical informatics from a large state school last year and have a b.s. In biology. Through the degree including research, several personal projects, and independent study I have built my expertise toward a bioinformatics software engineering (SE) focused job.

I realize it is often on a job by job basis but to help my additional efforts, if I am not already experienced enough what general skill levels in different areas would it be helpful for me to be at specifically in SE and math for a bioinformatics tool or research programmer or analyst (more mathematical but can be combined with others) new graduate job? What general percent balance of SE/Math/Bioinf. and other knowledge might be useful?

I'm not asking for one right answer for all jobs but in general just useful advice towards gaining this work. Advice on specific skills and not just general topics is appreciated. I know taking cues from job requirement listings help but your personal opinions help as well!

Answer 1

[Michael]

I think you should focus on your thought process first. It is hard to grasp what your question is about.

You should not focus so much on trying to obtain generalized answers because there is no good general agreement on required skills because there are no two identical jobs. For most jobs you are going to need the skills that are required to do the job. Whether these are the skills stated in the announcement is another question; if you are sure you have about 50% of the required skills for a position, you should apply, because good computation savvy people are hard to find while biologists there are plenty.

If you want some general advise: Focus on improving the weak spots. Therefore, I would recommend the following: focus on programming, math and statistics. These strengthen overall logical thinking and problem solving. If you excel in these, you can also master biological concepts easily and are able to learn new concepts and adapt to new challenges, while the opposite is not necessarily true for biology. Also, your career perspective will broaden to be applicable to other fields of IT and general SE, such that you can easily find a (non-scientific) developer position in the industry.

Some good complementary tasks given your profile showing already good knowledge of biology:

• Get involved in a data analysis project and give advise to biologists on experiment design and statistical analysis
• Answer questions on BioStar
• Take on software projects and write your own code
• Take on other people's software and try to understand, improve, and integrate and hack their code
• Maintain or contribute to software packages written in different programming languages than the ones you know already
• Document your code and other people's code
• Work in a team together with other people on these things
• Lead a small team of people doing these things

In addition:

• Do something else, diverge from the common well-paved ways. Don't take a completely utilitarian approach to your life, a mind-set of having to be of highest possible utility for the job.
• Play Real Time Strategy Games, they improve cognitive flexibility ;)

[wid2231auu1]

Thank you for the advice. To be more specific, my thought process is just to find what some of the most popular specific SE and math skills are currently for these jobs. I can appreciate jobs vary in their skills but any way I can optimize my efforts to stay relevant to recurring bioinformatics requirements is appreciated.

The complementary tasks you listed are useful options that can all help accumulate further experience relevant to the work, I have done some of those in the past and found the skills gained to be valuable. I also agree to focus on areas I could use more experience in including programming, math, and statistics but specific details about subareas of the subjects can help me. I'm accepting of any subjective viewpoints, personal experiences, or even educated guesses but some more information I am looking for is opinions on questions such as c/c++ vs c# vs java's more common use for high performance analysis software or if spending more time on javascript frameworks vs server side scripting languages vs Java has more helped with online tool web interface development. An example math question is if bioinf. programmers who are also analysts have found it important to learn deep calculus for data mining or have regression and more typical statistics have usually been enough.

I'm not attempting to take a too utilitarian approach to life but to be balanced about incorporating into my expertise well regarded abilities for the work to try to gain such a job efficiently.