Practical guide to ensure your supervisor is a catch, not a clash.
Last week, we talked about the importance of choosing a good supervisor to oversee your work, whether it’s for your bachelor’s /master’s thesis or your PhD. That piece of advice sounds wonderful just like that, but it might be even better with a few suggestions that you can easily implement when navigating the academic universe.
Because we know that, we bring you today the Practical guide to make sure your supervisor is a catch and not a clash.
First, let's clarify why this decision is more paramount than you might think.
What your supervisor controls (whether they mean to or not)
At the beginning, we think of our project supervisor as the person who will be in charge of signing our forms, deciding which kits we can buy and having a huge say on whether we can or cannot do a very expensive experiment.
However, as the project advances, we often find ourselves learning a whole set of soft skills from the person who is guiding us through the research maze. And that is because they control, among others:
- How feedback happens (and how often)
- Whether mistakes are treated as lessons or as personal failure
- How priorities are set in a fast-paced environment
- Your access to resources, collaborations, and opportunities
Taking all of that into consideration, it seems only logical to dedicate a bit of your time to looking into your potential supervisor and their team.
Without any further ado, here you have some things to consider when you are in a selection process:
First things first: interview the prospective supervisor
The best way of knowing is, generally, just asking (surprising, uh?).
Some questions that may help you understand how they run their lab are:
- “How is the team communication handled? How often do you have group meetings?” Whether the group is large or small, communication must be fluent, so you can benefit from everyone's perspective and critical thinking.
- “How do people organise during long experiments?" It's great to have responsibility for your own project, but it's even greater to know you can count on your peers' hands during round-the-clock experiments.
- “What happens after a mistake?” This may sound trivial, but believe me, it isn't. You are definitely not looking for a supervisor who punishes their workers as if they were children. When asking this question, pay close attention to the PI's first reaction. You can thank me later.
- “How are authorship and credit decided here? For example, who has the final say, and how do you handle situations where people disagree about contributions?"
- “How do you handle stalled experiments or changing priorities?” We all know it's not rare for an experiment to go differently from what we planned (we don't really like the term wrong, sorry), and it's always good to know what to expect in these situations. To know that you won't be all by yourself.
Analyse the whole ecosystem
You can find yourself at an interview where a supervisor talks great about how they manage difficult situations or deal with fast-paced environments. While this might be completely true to them, the reality perceived by their team might be slightly different.
And the thing is, a mentor's skill set will always reflect on their team's dynamics.
Here are some actions you can implement during the selection process that will give you a clearer idea of how good a leader the PI is:
- If you have landed a face-to-face interview, ask for an informal lab visit after the meeting ends. In my experience, supervisors hardly ever say no, and people from the lab are always willing to have a short coffee break or show you around.
- Speak to at least two lab members at different seniority levels. Do not let yourself be swayed by a single opinion, as seniority often implies getting to know different sides of the PI. Gather as much information as possible to see the bigger picture.
- If possible, speak to a former lab member. With time, things tend to acquire a different dimension, and we become more candid. You might find it more useful than you think to see how things ended for them.
Once you've been able to close a meeting, below are some questions that may come in handy:
- “What is something you found this lab to be different from others you've known or worked in?” This question is 100% neutral, and the person you are talking with will give it a positive or a negative connotation. And that, my friend, is as useful as the answer itself.
- “How easy is it to ask for help?” Great to know if you are dealing with an overall supportive ecosystem.
- “What does a normal week look like in practice?” There's a hidden enquiry in this question: "How often do you have to work long hours, and how stressful is this job?" Because we have mastered the art of questioning here.
- “How are conflicts handled?”
- “Would you join this lab again?” This question might sound controversial, but you'll be surprised by how honest people can be when they have the opportunity to change others' fate.
Overall, always look for consistency: does the PI’s description match the team’s lived reality?
Signs your gut should run vs signs that give 'good for your mental health' vibes
Healthy vibes ✅
- People describe daily dynamics clearly and consistently.
- Lab members speak freely (and don’t look over their shoulder constantly).
- Workload sounds intense sometimes, but not as a permanent identity.
- Credit and authorship norms are transparent.
- The lab is proud of good science without leaving human consciousness aside
Run 🚩
- Vague answers to basic questions (“We’ll see how it goes”).
- Reactive-moce culture: always urgent, always behind, always firefighting.
- High turnover with awkward explanations.
- You’re told you need to be “tough” to survive the lab.
Hopefully, this overall analysis will help you to avoid PIs who fall into alter ego categories 1-3 (if you don't know what I'm talking about, you need to go to The Modern Peer's last week's post 😉.
And if you only have one offer? You can still ask questions, set boundaries early, and enter with eyes open rather than hopeful and blind.
Comments ()