A Day in the Life of a (Biostatistics) PhD Student
Today, I thought I would share what a day in the life of a PhD student is like. Personally, I’ve always been interested in other people’s day-to-day experience at work. So I imagine that similarly, getting a glimpse into my day could be interesting and informative, particularly for students thinking about getting a PhD in biostatistics.
I took two days from my third-year calendar (i.e. pre-pandemic) to give a sense of not only the typical activities I do, but also show how each day can be drastically different. The two days I’ve chosen below are polar opposites in that on Wednesday, I spent most of my day alone doing research, while on Thursday, I had a lot of meetings and other obligations. Usually, my day lies somewhere between the two extremes.
Before I go into the details of my schedule, I just want to note that these two days are pretty much the busiest I ever get. Especially in the later years of my PhD, I’ve become much stricter about my working time (for example, I don’t work after dinner anymore). There is a lot of freedom and flexibility with respect to time in academia, which can be a double-edged sword, so it’s important to figure out what the right balance is for yourself.
Wednesday - A Day of Research
- 8:30AM Meeting - This was a research meeting for a collaborative project with some colleagues in India (hence the virtual meeting in pre-pandemic times).
- 9:30AM E-mails - I usually set 1~2 times in my schedule specifically to check and reply to e-mails, so that I’m not constantly distracted by my inbox. This can happen at the beginning of the day, the middle of the day, and/or the end of the day.
- 10:00AM Gym/shower - Some things to function as a human being.
- 10:50AM Blog - Since I was working on an R package for one of my projects, I felt like it would be useful to write a brief tutorial on the blog at the same time.
- 11:15AM Research - During my research time, what I literally do consists of writing R code (to clean data, run analyses/simulations, build models, or make plots), reading (about statistical methods/tests and other relevant literature), or writing (making slides or drafting the manuscript), more or less in that order from most frequent to least frequent.
- 1:00PM Lunch - Something else I have to do as a human being: eat!
- 1:20PM Research - It’s always great when I get an entire afternoon to work on research uninterrupted, so I take advantage of these times to work on the most cognitively-intensive or otherwise time-consuming research tasks. This afternoon, I was working on two projects: fragmentation, a project where we analyze cell-free DNA to detect cancer, and signatures, a project where we identify mutational patterns in the cancer genome. The latter project has since been published here. I will also talk more about my dissertation research in a future post, so stay tuned!
- 5:30PM Dinner - Time to eat again. I usually cook for dinner, especially when I’m already at home during the day.
- 6:30PM Research - This was the third research project I was actively working on then. I think the maximum number of projects I can juggle at once is three. Beyond that, the research time:meeting time ratio becomes increasingly difficult, since the more time I spend in meetings, the less time I have to actually work on any research updates.
- 7:30PM Blog - Blogging can take quite a lot of time, but it usually feels worthwhile because I only ever write posts that I have an interest in writing in the first place!
- 10:30PM E-mails - I wouldn’t usually check my e-mail so late at night nowadays, but I hadn’t yet figured out how to block off my time yet in my third year.
Thursday - A Day of Meetings & Teaching
- 8:15AM Commute - I take a shuttle to get to campus. The bus ride itself is about 20~25 minutes, but in total, the commute is 45 minutes~1 hour door to door. Even before the pandemic, most PhD students had a hybrid schedule, in which you only have to go to campus for meetings and classes, but are otherwise free to work at home or on campus, depending on personal preference. So on Wednesday, I stayed at home, but today, I went to school.
- 9:00AM Meeting - I was a representative for the biostats department on the Doctoral Student Council. It’s a cross-departmental organization consisting of PhD students, where we meet to discuss how PhD students’ lives can be improved regarding things like benefits, TA policies, social activities, etc. It’s generally pretty casual and a good opportunity to meet PhD folks outside your own department.
- 10:00AM Admin stuff - This is the miscellaneous stuff that people don’t really think about, but it still takes time to do! The things I had to do were to print out slides for my TA session later in the day and then drop off a receipt for reimbursement.
- 10:15AM TA prep - For my TA prep, I mainly review the slides and make sure I understand everything that’s being covered so that I can actually teach it to my students. All the TAs use the same set of slides in their lab sessions so that the content is more or less standardized. Having said that, the slides just provide a base structure and we have the flexibility to teach however we think would be most effective.
- 11:00AM Meeting - This was a larger research meeting for the fragmentation project, consisting of multiple labs. Such meetings can sometimes take longer and run overtime if multiple people have something they want to discuss.
- 1:10PM Lunch - I grab a quick bite to eat on campus on the way back to my office. I have two office locations on campus, one in the School of Public Health (where all biostats students have offices in) and another one in the cancer center (where my advisor’s primary appointment is). The two buildings are about 10 minutes walking distance apart, so sometimes I have to make multiple short trips going back and forth throughout the day. It’s not really an inconvenience, just something you have to budget time for. Side note/pro tip: there’s a maze of passages underground at the medical campus, which is convenient during bad weather.
- 1:30PM TA prep - I finish prepping the material for my TA session.
- 2:30PM E-mails - In these shorter blocks of free time, it can be hard to do anything substantive research-wise, so instead, I just respond to some e-mails. I also returned a hard drive that belonged to a collaborator, which I had borrowed to copy over some data they had sequenced in their lab. We wanted to try applying the methodology we developed in the signatures project to analyze their data.
- 3:30PM TA - I teach the lab session for the statistics sequence at the School of Public Health. Generally, about 20~40 students attend the labs. Sometimes, students will ask a lot of questions and other times, they won’t, so you never know what exactly to expect, even when teaching the same lab lecture (read more about my experience as a TA here). The lab is technically scheduled until 4:50PM, but sometimes, I finish earlier than the allotted time, like today.
- 4:30PM Commute - The shuttle ride back home usually ends up taking longer because I can’t get my timing to match as well with the shuttle schedule.
- 5:30PM Research - This doesn’t happen very often, but today is one of those days where my schedule is so filled with other things that I don’t get around to research until the end of the day.
- 6:00PM Dinner - I’ve been a bit facetious about having to eat to live as a human being in this post, but it’s worth noting that given the lack of a set schedule in academia and the relative isolation and independence of most graduate students, it’s possible to neglect these life-sustaining activities, so you need to remember to take care of yourself.
- 6:45PM Research - Again, I rarely work after dinner nowadays, but it was something I did more frequently in my earlier PhD years. As a postdoc once told me, a PhD is a marathon, not a sprint, so managing your time off is just as important as the time you spend working.
If you’re interested in a day in the life of a working biostatistician in academia, I recommend reading Katherine Hoffman’s blog post. In particular, she goes into more detail about her research projects, if you’re curious about what research in biostatistics is like.