Working on a cross-disciplinary project, in an increasingly cross-disciplinary field, I often find myself wondering whether or not I am developing skills in multiple different areas of my work. I intend this question to be as general as possible, but for the sake of clarity I will give my case as an example:
I have a MSc in applied mathematics, and have been working with biomedical research for three years now. Being branded as a bioinformatician I feel very appreciated on one hand, and absolutely disregarded on the other. In many cases I am expected to learn more of the biology and develop an understanding of "the real science" while all the tools and analysis should just work. I mean many of the seniors have absolutely no idea of the time and effort it takes to develop at software tool, maintain and further develop it. It appears as all that is given once and for all in the engineering school, after all programming is just programming... (please note the sarcasm here)
Be as it may, I have been trying to improve my knowledge and experience in the technical aspects of the work on my own; learning new algorithms, new languages, new tools... It is surprisingly hard to get accustomed to these when you are not in the university anymore. Consequently, I have given up on learning Maven for my Java projects, or Perl for speeding up my day-to-day scripting.
So my question is; what are good methods for learning or developing techniques that are not immediately in the scope of your project but is still very relevant in your development as a scientist?
Follow up question: am I mistaken in thinking that I should develop a broad set of skills in order to become as efficient and competent as possible?