Barry Ryan

Barry Ryan (PhD 2021–2025) developed integrative methods to combine multiple biological datasets and model patient relationships using networks, improving disease prediction and interpretability. He is now a Postdoctoral Researcher at EPFL’s Fellay Lab, working on human genomics of infection and immunity.

PhD start and end years	2021 - 2025

What was your PhD research about?

My PhD investigated ways to integrate multiple biological datasets and model patient relationships using networks. Intuitively, different biological dataset will capture different aspects of disease and patients with close relationships will have similar disease outcomes. My PhD aimed to combine these entities to improve patient disease prediction and interpretation.

What motivated you to undertake doctoral study?

Deciding to undertake doctoral study was a series of incremental steps for me. I flirted with the idea of a PhD during my undergraduate degree, but I was never sure what I would study or what it really meant to be a PhD researcher. In the end, it took 3 months in industry to understand I wasn’t done with research. I signed up to a MSc course and undertook a project in Biomedical Sciences in Dublin, Ireland. This led to me search for Biomedical AI doctoral programs, and the stars seemed to align, as this was the exact course Edinburgh were offering.

What was a highlight (one or several) of your time as a doctoral researcher?

Preparing and presenting a workshop at ISMB in Montreal in 2024. This was such a fun experience getting to share some of the group’s work. It’s true that you really can’t understand a topic until you can teach it.
Delivering my first oral presentation at ENGOGS in 2023. My first oral presentation of my PhD, as well as my first oral presentation in person post Covid. My heart rate sky rocketed, but the experience to present at a local conference gave me the confidence to take on bigger challenges – highly recommend. Finishing the evening with a beer and a nice dinner with some close friends was the perfect end to the day
Board games evenings. Once a month as a group we got together as a lab group to hang out and take on some social (and sometimes competitive board games)
The 7 hills challenge with Thibaut, Wolf, and Rodrigo. For more information ask for Wolf/Rodrigo the runners in School of Informatics. You may or may not regret it!

What challenges did you face, and how did you overcome them?

No knowledge of biology, lack of ChatGPT for my first 2 years, Zoom classes, GitHub merging conflicts, etc… It’s a long list. From an observational perspective of my experience and that of my peers, the greatest challenge during a PhD is navigating the relationship with your supervisor. Every supervisor is different, and not every supervisor will suit every PhD student. Finding the right supervisor for you will depend as much on your personality as it will on the research area you undertook. Understanding that a supervisor is a mentor and someone to guide you when you are lost as opposed to a boss can be challenging but is so important. Thankfully, I think I had the best supervisor in the world, but I may be biased.

What are you doing now career-wise, and how did your PhD prepare you for it?

I am currently a PostDoctoral Researcher in the Fellay Lab of Human Genomics of Infection and Immunity at École Polytechnique Fédérale de Lausanne in Switzerland. At the beginning of my PhD, I was told that a PhD is a training program, and this fact is probably the most important perspectives shifts I had during my PhD. The training I received in University of Edinburgh was world-class, from both academic staff, but also fellow students. Beyond training in my research area, my PhD also taught me to be more confident and proactive in my research, even if that means failing more than succeeding.

What’s one key skill or mindset you developed during your PhD that you still rely on today?

Hard work. Make no mistake, a PhD is challenging with no straight simple paths and many ups and downs. Unfortunately, despite all our fancy AI algorithms, adopting a brute force mindset, for me, is so important. Be willing to accept that the same code you ran on Monday is now broken on Wednesday, but your results on Tuesday are somehow better than those on Friday. The line between success and failure is sometimes out of your control and can be hard to accept.