What I Wish I Knew Before I Started Grad School
The journey to grad school was an uphill battle. In my junior year I received 3 concussions from playing collegiate football. My midterms had to be deferred and my GPA suffered. I applied to 10 graduate programs and received 10 rejections. This led to the decision to take a 1-year undergrad extension to boost my GPA. When it came time again for graduate school applications, I took an aptitude test to demonstrate my knowledge to the admissions board and found a senior scientist who was willing to take a leap of faith on me as a grad student in her lab.
In the end, I was accepted and scheduled to begin my grad studies the following fall semester.
Getting into grad school was one of the happiest moments of my life. I started out as a bright-eyed, eager, young scientist with dreams of doing high-impact research. Yet after working so hard to get into my M.Sc. and grinding through it to reclassify into a Ph.D., I never knew I would go on to leave grad school 3 years later to build a company.
In many ways this post isn’t about tips and tricks to help you succeed in grad school. It’s a recount of how I stood at a fork in the road, choosing between completing my research and pursuing my (new) dream. Here are the things I know now, having gone through it all, that I wished I knew before I got started.
Start with the end in mind
Why are you here?
Is grad school the first step in your path to becoming a professor? Is it the training you’re looking for to make the leap into the biotech industry?
What are your next steps after grad school?
Knowing what your next steps are informs you on how to pick an appropriate graduate project, what skillsets you are looking to develop during your grad school training, and what preparations you need to make for the next stage of your career.
Decide what kind of risks you are willing to take
When you first start, you will have some time to read literature, get advice from your peers, and ultimately, decide on a research project. The more simplistic your project, the easier it is to get results and data. The path to results are often more clear, but it will likely not yield the juicy novel research you need to land a high-impact publication.
If you’re aiming to run your own lab one day and become a professor, chances are you are looking to achieve high-impact papers in your Ph.D. Maybe this means you have to leverage new techniques, or learn computer programming and data science to tackle the much dreaded bioinformatic realm. One thing is certain though, the more complex and novel your project, the more abstract the experimental methods are, which often results in a high-risk high-reward situation.
What happens if you don’t end up staying in academia?
There is no question that having a graduate degree is a testament to your intellectual capabilities and work-ethic, but unless that graduate degree has relevance to the job you are applying for outside of academia, it’ll likely not contribute in a meaningful way to your future endeavours.
If you know that you are not planning to take the PI-route, find a project that will allow you to develop the skills you need to be industry-ready right when you graduate. I would highly advise to pick a project that has a very clear and concrete experimental path that aligns with what you want to do next.
Ultimately, starting with the end in mind, is a mindset that you need to adopt on day one of grad school. Every experiment you decide to do requires your time, and it’s on short supply. You need to graduate within 5–7 years.
If you know you want to stay in academia, be ambitious and take the risk. If you know you’re going to be pursuing other things after grad school, be pragmatic and get it done.
Put your graduate journey into perspective
Keep in mind that you are entering and completing grad school during one of, if not, the most transformative and consequential periods of your life. Typically you are starting grad school in your early 20s. From bachelors to masters to doctorate, you are looking at about 7–10 years.
If you were like me, a grad student in an expensive city like Toronto, income is low and expenses are high. The struggle is real, to the point where “Can I afford rent this month if I buy this $3 cup of coffee, so I can stay up to finish this experiment?”, is a real question.
What makes this even worse is the fact that no matter how much you work, you will still earn the same. No matter how much effort you put in, there is still a strong chance your experiment will fail. No matter how careful and methodical you are, there is a chance something beyond your control, like a tissue-culture contamination outbreak in your facility, can set you back 6 months.
Research is lonely
When my experiments failed, I was frustrated, angry, and experienced a range of 10 other emotions. The challenge is no one understands your project except for you, so how can you explain it to your significant other, family and friends what the problem is? How can you expect them to be able to help you? You are literally discovering new things in an ultra-niche space of human knowledge. Very few people will understand and it is lonely.
You’ll look at your calendar and realize you have a committee meeting scheduled in a few months but you don’t have enough data. You’ll attend a friend’s wedding and when you tell people you are a Ph.D student, you’ll hear “Oh wow!”, but inside you feel like a fraud because your project is not working and you don’t know if you’ll graduate. There will come a time, when you will feel like you are grinding all day and night, but are getting nowhere.
The tunnel is long and dark but at the end, there is light.
For all the struggles, the late nights and the ups and the downs, I would do it all over again. Knowing what I know now, I should have been a little smarter when picking my research project, prepared to handle tough patches and planned out how to work more efficiently.
All things considered, going through grad school gave me the skills and knowledge to do what I do today.
I believe, that the foundation of a strong scientific community, is built from the efforts and fortitude of our graduate students. They are the ones in the lab 80 hours a week, persevering through it all, to push the boundaries of science.
But honestly, it doesn’t have to be this way.
Graduate school shouldn’t feel like you are chewing glass for 5 years. There are so many things that we can do to make research, as a whole, smoother and more efficient. Beyond the obvious systematic issues with grad school financials, a lot of the time it’s the opacity of the data, the lack of tooling and the unstable infrastructure that makes research so frustratingly difficult.
This was one of the reasons I decided to leave it all behind to build BioBox.
I left a lot of good work on the table that I still, to this day, have dreams of finishing one day. But seeing all the problems my colleagues and I faced, I knew I had to build something that would have made my own research and the research of my colleagues easier.
To clean up the problems that everyone in my field knew about but didn’t really talk about.
And to provide solutions for problems that we’ve just learned to live with because it seemed like it couldn’t be solved.
Over the next few weeks, the team and I will be releasing a series of blog posts on our medium publication. We will delve into each team members’ journey to BioBox and explore why we do what we do — tune in for Part 2, launching November 30th, 2020.
We hope you follow us along on this short, but sweet journey — just in time for the holidays.
To learn more about BioBox Analytics, visit our website.
BioBox is a data analytics platform designed for scientists and clinicians working with next-generation-sequencing data. Design and run bioinformatic pipelines on demand, generate publication-ready plots, and discover insights from your processed data. Learn more at biobox.io.