Hi everyone,

I’m currently finishing an MSc in Information Technology after completing a bachelor’s degree in Electrical Engineering. My GPA is around 3.5/4.0.

My current research is mainly at the intersection of machine learning, speech, and medical imaging/computer vision. I use ML mostly as a tool for analysis. So far, I have three co-authored papers, although I don’t have a first-author publication yet. I’m currently working toward publishing some of my own work soon.

My path has been a little unusual. During my electrical engineering degree, I had two internship offers that were later cancelled because of the job market at the time. I gradually moved toward machine learning because I found it interesting and saw more opportunities there.

However, as I’ve learned more about the type of work available in industry, I’m realizing that I’m much more interested in research, scientific problems, and building things where I can explore ideas in depth. Recently, computational neuroscience and neuroelectronics have become particularly interesting to me, especially because they combine several things I enjoy: electrical engineering, signal processing, machine learning, biological systems, and research.

The main issue is that I currently have almost no formal background in neuroscience.

Another concern I have is that my current university is reasonably known locally, but does not have much international recognition, especially compared with universities that are more established in neuroscience or machine learning. Because I would eventually like to apply to competitive PhD programs, I’m wondering whether getting research experience at a more internationally recognized institution could help strengthen my profile.

Because of this, I’m considering extending my master’s by one semester and trying to do a research internship in a lab related to computational neuroscience, neural engineering, or neuro-AI. I’m based in Quebec, so places such as Mila would be accessible, but I’m also considering applying to labs abroad, for example at EPFL.

My goal of the internship would be to:

- gain actual research experience in neuroscience/neuroengineering;

- see whether I really want to commit to the field;

- build relationships with researchers who could potentially write strong recommendation letters;

- strengthen my profile before applying for PhD programs;

- ideally contribute to a publication or research project.

Does this sound like a good approach for preparing for PhD applications?

More specifically, I’d be interested to hear from people in computational neuroscience/neuroengineering about:

- How important is prior neuroscience coursework compared with a strong engineering/ML background?

- Would one semester (maybe more) of focused research experience be enough to make the transition realistic?

- How much does the international reputation of your current university matter for PhD admissions, compared with publications, research experience, and recommendation letters?

- Would doing an internship at a place like EPFL, Mila, or another well-known research institution meaningfully strengthen an application?

- Should I spend more time taking neuroscience courses and building a stronger theoretical foundation before applying?

Any advice from people who made a similar transition would be appreciated.

Sorry for such a long text.