Anjali Gopal is a PhD student in Bioengineering at the University of California, Berkeley. You can follow her on twitter at @anjali_gopal.
My first substantial research experience was in a genomics lab, where I wanted to dig into the booming world of bioinformatics. I was green, green, green, and determined to prove my competence: I was going to be a computational expert, build systems from the ground up, and do the type of analysis that would change the face of cancer and antibiotics resistance and heritable disease.
“You could take a look at my pipeline, and modify that for one of our other projects,” suggested my graduate student mentor. This seemed like a good, concrete deliverable -- very similar to the types of things I had done in industry -- so I agreed. I told my supervisor that I was less interested in publishing and more interested in gaining skills. It was a noble goal, and everyone in my lab was friendly, supportive, and knowledgeable. However, I missed one crucial component: I had joined this lab to figure out if I would enjoy graduate research and yet, in my one year in my genomics lab, everything I was doing was much more reminiscent of a laboratory technician than a graduate student.
When we start a project, it’s easy to get caught up in the trenches: we must figure out what types of literature to read, organize the types of experiments we want to run, determine which hypotheses to evaluate, and so on. However, even when we do this, there are key ways in which we can miss some of the higher-level goals in doing good, graduate research.
For instance, consider my experience with computational research. For a long time, I thought computational biology involved building pipelines to do genomics analysis using pre-existing software packages. It wasn’t until six months into my lab work that I realized that computational biology was actually about developing new algorithms to do genomics analysis - an area that I hadn’t even considered. Similarly, when I started out in graduate school, I thought I should primarily focus on literature that was directly related to my project. However, it wasn’t until I started talking to senior graduate students that I realized that breadth in literature (reading broadly across your field) can often be as important as depth.
In each of these cases, it seemed like the work that I was doing was Useful and Good, and I think this is precisely why graduate-level research is so hard: it can feel as though you’re making progress on meaningful work, and, with long feedback loops, you might not know that you haven’t been making progress until months down the line.
So, what are ways we can prevent pitfalls like these? One obvious solution is having good mentorship -- good advisors and graduate mentors can often steer you toward better research strategies than if you were going about it yourself. However, an advisor can only do so much. For instance, unless you discuss your literature-reading habits in detail with your advisor, it may take repeated instances of trouble before you realize you should be increasing your reading breadth.
Another option is to ask meta-level questions about research strategies.
Asking specific questions about the type of work you’re doing, how you go about doing it, and what sorts of avenues would be meaningful, can often provide a wealth of knowledge that it might take you several months to figure out individually. Moreover, the people you’re asking -- your mentors, advisors, and other senior graduate students in your group -- can often speak from their own experience (and even from their failures!) to guide you.
I did just this when I started work in my graduate group this year. I asked my professor questions such as “What sorts of things have graduate students done particularly well?” or “What the top three characteristics of productive graduate students?” You can also ask the same questions in a different angle to get additional feedback, such as “What sorts of struggles can I anticipate running into?” or “What might I be missing?”
Learning from others’ failures means that you don’t repeat the same failure yourself. Often, it may seem like you need to witness this failure in order to avoid it -- but that’s not true. With the right questions, you can tease these out for yourself and, with the right questions, you can learn how to avoid them preemptively.
[Image by Flickr User linkhumans, used under a Creative Commons License].
Read more by
You may also be interested in...
Opinions on Inside Higher Ed
Inside Higher Ed’s Blog U
What Others Are Reading