I am currently a third year PhD student in Neuroimaging. My project is divided evenly in the neurosciences and in medical imaging, specifically diffusion MRI, and is purely dry-lab. My work requires computational, programming, statistical and a bit of physics knowledge to effectively tackle research problems in this area. Before my PhD, my honours year involved drug discovery in the parasitology field. I changed from wet-lab to dry-lab after my Honours because I didn't like wet-lab research and was much happier crunching numbers on a computer.
I am very interested in making a switch to computational biology after my PhD because I love biological/clinical research problems and I would like to apply or develop my computational skills in the biology field, as opposed to imaging physics.
I have a few questions to ask from researchers/professionals in computational biology regarding this topic:
- I understand that I will need to get up to speed with the computational skills needed in computational biology. I'm more interested in applying the skills to answer research/data problems, rather than developing software/algorithms without a research focus, so training wise, should I apply for formal qualifications after my PhD (i.e. a Masters in Biostatistics) or gain such knowledge through online training (i.e. Coursera and Rosalind)?
- I am used to learning by doing the programming and statistics and teaching myself the computational skills needed for the problem. I do understand the argument that teaching yourself these computational skills is much more valuable and insightful than a University course, however, I would like to apply for computational biology Post Doc positions in the future. Given this aim, would a formal qualification be better in the long run than taking online courses (even with online certification)?
I've browsed this forum for topics similar to this one that I'm posting and I did find a topic with some great answers: (How to switch from bench research to computational biology?), however I'd like some feedback into my own personal situation.
Thank you!
What skill sets are necessary to neuroimaging in general? Thank you.
What skill sets are necessary to neuroimaging in general? Thank you.
In Neuroimaging, you need to be prepared to work on a Unix/Linux system and to learn Bash Shell Scripting and programming to run the commands necessary to run imaging software. With different imaging modalities (i.e. dMRI, fMRI, PET, MEG, EEG), you'll have different methods but the computing environment is the same if not similar. You should also have knowledge of neuroanatomy, which you'll gain if you run your analysis often enough, and you should have a basic idea of how the scripts for your imaging method work so that you can tweak them if they don't work as they should on your imaging data. So the basic computational principles of good data management and patience when programming/running and designing your pipeline apply here too.
I don't know anything about neuroimaging but from the way you describe it I would say you are already in the computational biology field! Maybe what you mean is how to enter the subfield of (next generation) sequence analysis, which is currently the main branch of computational biology/bioinformatics but it's by no means not the only one (others please correct me if wrong...).
With these skills I would just follow Jean-Karim Heriche's advice: Just apply for a project you find interesting and be prepared to learn new topics.