For the last few years I've given a talk to incoming Ph.D. students in Molecular Biology on why they should consider doing Computational Biology research. I'm fairly passionate about making this pitch, since I strongly believe all 21st century Biologists should have a greater (or lesser) degree of computational training, and that the best time to gain that training is during a Ph.D. or a Post-Doc.
I've decided to post an expanded version of the reasons I give for why Biology trainees should gain computational skills in hopes of encouraging a wider audience to consider a research path in Computational Biology. For simplicity, I define the field of Computational Biology to include Bioinformatics as well, although there are important distinctions between these two disciplines. Also, I note that this list is geared towards convincing students with a background in Molecular Biology to consider moving into Computational Biology, but core aspects and variants of the arguments here should apply to people with backgrounds in other disciplines (e.g. Ecology, Neuroscience) as well. Here we go…
http://caseybergman.wordpress.com/2012/07/31/top-n-reasons-to-do-a-ph-d-or-post-doc-in-bioinformaticscomputational-biology/
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