Gonçalo Ferreira - PhD profile

Can you tell us a little about yourself and where you’re coming from, both academically and geographically?

I was born and raised in the north of Portugal, having completed both my Bachelor’s and my Master’s in Porto, at FEUP. I studied Bioengineering, with a specialization in Biomedical Engineering. During my academic journey, I took an interest in applying software and machine learning to medical problems. Through a couple of internships at different research institutes like INESC TEC, INEGI, and at the University of Gent, I had the opportunity to delve more into medical imaging and deep learning.

What motivated you to pursue a PhD, and what drew you specifically to Endotrain as a doctoral network?

My main motivation towards pursuing a PhD was feeling like I could contribute more to the state-of-the-art research in the medical technology field. During my MSc, I discovered my interest in innovation, and a PhD could provide me the tools to better understand how to do quality research and explore new potential disruptive technologies.

ENDOTRAIN seems like the perfect setting for that end, as the doctoral network is part of the MSCA programme, which highly values collaboration between industry and academics. It also promotes cooperation between the different positions in the network, which I believe is fundamental to develop robust and useful systems. In particular, the focus of the ENDOTRAIN network seemed really interesting to me, as digital endocrinology is a largely unexplored field with enormous amounts of potential.

Where will you be based during your PhD, and what are you most looking forward to about living and working there?

Even though my PhD institution will be the University of Bergen, I will be moving to Sevilla, Spain, to work at Adhera Health. I will also have three secondments, at the University of Bergen in Norway, the Karolinska Institute in Sweden, and University Hospital Zurich, in Switzerland. I’m very grateful for the chance to learn how research is conducted at all these incredible institutions. I’m looking forward to learning how medical technology is developed in both industrial and academic settings, while exploring the cultures and ways of living across Europe.

At this very early stage, how would you describe your PhD project in broad, non‑technical terms?

In a nutshell, my project is based on developing technologies to combine different sources of data in an aggregated and structured model, as a tool to help with diagnosis and treatment of adrenal diseases. These sources can be clinical reports, or data derived from wearables developed by the other students in the network, for example. From those models, the project also aims to develop useful and usable interfaces to help both clinicians and patients make more informed decisions.

During your PhD, what specific skills, methods, or areas of expertise are you most looking forward to learning?

While I do have experience in deep learning, it has been mostly directed at medical imaging. As such, I am looking forward to learning more about multimodal data fusion, and how language models can be used for clinical decisions. The medical field is very diverse and broad, and any model used in practice needs to be designed with that diversity in mind, so that information from many possible sources can be correlated and contextualized.

As part of the MSCA program, there is also an interested in developing soft skills related to scientific communication, which I am hoping to develop further. I believe being able to explain our research to a broader audience is not only valuable for the scientific and technological literacy of our community, but it also facilitates adoption and use of the developed tools. 

What are you most looking forward to about learning and working within an international doctoral network like Endotrain?

Understanding where the data comes from and what is means (also known as domain knowledge) is fundamental to developing good models. As my project is downstream from the other positions in the network, I hope to learn how the data is generated and what it means in practice. On a more personable note, I also love learning about different scientific fields and the people working on them. Since ENDOTRAIN is such a diversified network, I look forward to meeting lots of interesting people and knowing their stories.

What do you enjoy doing outside of work that helps you relax and recharge after a long day of research?

I’m a huge gamer. When I need a break from research, I like spending some time playing indie games, or getting my VR headset. I also work out regularly, either through resistance training or casual walks in nature with my dog. On the weekends I try spending time with my family and friends, either in a bouldering session or in dinner parties.

As you begin your Endotrain journey, what are you most curious or enthusiastic about right now?

Working in a new and emergent field such as digital endocrinology is very exciting. I believe the collaboration between industry and academic institutes will be a key to seeing the rapid development of tools that can be put into practice, and potentially help save lives. I can’t wait for the official ENDOTRAIN project kickoff in Zurich.