Supervisor Selection: Applying for Research-Based Graduate School

Finding a supervisor can vary across academic institutes. For example, your acceptance into a graduate program may only be granted after you have secured a supervisor (not before). In other instances, it might be best to wait until you are formally accepted into the program before contacting professors, since it’s an easier process for them with you already being vetted. These professors will also have access to your application materials which can help streamline the process. Furthermore, professors may reach out to you first for an interview.

When selecting a supervisor, consider:

1. Research Interest Overlap

2. Type of Degree  

3. Funding

4. Additional Opportunities

5. Working Relationships

1.     Research Interest Overlap

As an undergraduate student you may have broad interests in research areas which have led you to consider specific programs. Try to narrow your search as best you can. Consider reading the profiles of a few professors within a department of interest to help identify keywords to use in your search at other universities. You can also focus your search by disease type i.e., breast cancer versus pancreatic cancer; or an organ system component e.g., the cardiovascular system, but focused on the heart versus blood vessels.  There are also levels to the types of research you may conduct. Research can be considered basic science (discovery, bench work, cell/animal models), translational (more animal models/drug delivery/application based), or clinical (patient data, large studies). There are also wet labs versus dry labs, the latter being more prominent in disciplines like mathematics, computer science, genetics etc. More and more, research areas are becoming interdisciplinary and multidisciplinary, so there is increasing opportunity to expand your learning once you’ve settled into a project or program. Studies with artificial intelligence and machine learning are also a novel way to bridge disciplines. If these are of interest to you, consider faculty who may work in your field of interest, but also use these AI/ML principles in their research.

2.     Type of Degree

Research-based programs will offer either a Master of Science (MSc) degree or Doctor of Philosophy (PhD). A Master program is a two- year full-time commitment, whereas a PhD is a minimum of 4 years, however the latter widely varies. Both programs have their own benefits and advantages, as well as disadvantages and drawbacks. A full comparison can be found under the post "Program Selection”. When selecting a supervisor, visit their website and look at drawbacks of their students. Is their lab mainly PhD or MSc students? A mix of both? Only postdocs? It can be tricky to start in a lab with mostly PhD students as a MSc candidate, since sometimes PIs don’t have “two-year” projects. My experience: I entered a lab like this, and ended up transferring to a PhD program, as did another lab mate. The projects we were given as MSc students weren’t really designed to be completed in two years, they were much broader and designed for a longer-term commitment. Moreover, I have seen some students take 3+ years to complete their MSc– not the norm. Also, if your goal is to do complete a MSc then apply to medical school, you want to find a supervisor who is onboard with this timeline. Some programs might only be part-time after 2 years are complete. The same applies to PhD completion times and outcomes. Some labs are notorious for longer than average completion rates, so be diligent in your search for the right lab, especially if you are changing institutions.

3.     Funding

For the minimum years required for the degree, all graduate students are required to receive a full stipend (i.e., yearly salary). The funding amount will vary amongst institutions, but is usually a base minimum for both domestic and international students. For some programs/universities, students may need to work as teaching assistants for undergraduate courses as part of their stipend. In other cases, working as a TA is considered supplemental income to the stipend. Furthermore, students are often encouraged to apply for scholarships and awards to reduce the financial burden of the supervisors – however know that obtaining a graduate position should NOT be contingent on successfully bringing in your own funding. With the increasing number of unsuccessful grants and the enhanced competitiveness to secure funding, some students have been told they can only be taken into a lab if they are able to secure external funding. This is not the right approach and not someone you ideally want to work with.  Consider looking up your supervisor of interest to see their funding history (i.e., [PI NAME] + [GRANT AGENCY]). Ensure that the prospective PI can fund you for the minimum years of your program (you can also confirm this during the interview). Once in your degree, if your timeline to completion is longer than the minimum years funded, most departments should have resources to support your stipend until you finish e.g., a doctoral completion award.

4.     Additional Opportunities

Outside of the research you conduct in your lab of choice, you may have the opportunity to explore research-adjacent endeavors. For example, if your PI also has their own company or patents, you could be exposed to aspects of commercialization, entrepreneurship, and research design. If you plan to pursue an industry-based career, this type of lab environment can be beneficial; maybe you end up working for your PI’s company or they invest in yours. Additional opportunities can also mean access to diverse research groups, conferences and people – all of which can impact your research perspective, challenging you to expand your thinking, and grow as a scientist.  Finally, something as straightforward as the opportunity to be a teaching assistant (if not mandatory for your stipend) can be wonderful, especially if you are interested in teaching stream careers. During the interview with your prospective PI (or if you chat with their students) ask about such opportunities. Some supervisors may not want you too heavily engaged in activities that take you away from the lab (e.g., extracurriculars, teaching, internships etc.) so know before you begin.

5.     Working Relationships

When deciding which lab to join, and which PI to have support you over the next X number of years, consider what supports exist within the lab. First, consider the size of the lab. If the lab has over 20 people, it might be hard to always have one-on-one meetings, and sub-group meetings might be the norm, with private meetings only available for special circumstances. In a very small lab without any full-time staff (e.g. senior research associates or lab technicians), you will be responsible for more tedious tasks and might need to independently learn techniques. Second, consider the makeup of the lab. As mentioned, are their senior staff members and postdocs who can help you with troubleshooting experiments, or will all your support only come from your PI? When interviewing, I would recommend speaking to other graduate students one-on-one or in a small group, as they are more likely to be candid in an intimate setting. When you meet everyone at once, no one points out red flags. Third, think about the career stage your PI is in: early, mid or established. This may impact their availability as they may undertake more teaching or administrative tasks as they progress in years of service, but the reverse might be increased pressure from a pre-tenured PI (as they are actively trying to secure funding/tenure). Finally, what level of engagement and supervision do you want – someone hands off or hands on? Now this will vary as you also progress through your degree, but again, checking in with current students in the lab is a good first step in knowing which lab is best for you. Remember, you want to set yourself up for success.