With the Chateaubriand fellowship, I joined a team of researchers who were not only pushing the field of cognitive neuroscience with cutting edge analysis techniques, but were also deeply committed to creating a community for fellow researchers to discuss, share, and improve open-source data analysis software. During my fellowship year, I was supervised by Alexandre Gramfort who is the project lead for MNE, a python package for MEG and EEG data analysis and visualization, and a core contributor to scikit-learn, a python package for machine learning.
I spent my fellowship year learning how to introduce machine learning into neuroscience of language research to better understand the relationship between eye movements during reading and their underlying brain responses. At the same time, I continued my involvement as an MNE contributor to improve its support and introduce new tools. This fellowship year, for me, was a necessary boost to my PhD studies. As a neuroscientist, Chateaubriand allowed me to collaborate with engineers, and learn new skills that weren’t offered in my department.
In addition to being a great place to learn, Paris is perfectly positioned a researcher who likes to explore in their free time. Throughout my fellowship year, I would take the train on the weekends to explore France: I went champagning in Reims, I traveled to Chamonix to see Montblanc, I went down to Toulouse to go hike the Pyreenes with a friend, just to name a few. There are plenty of countries close by to visit too. The flights are quick and can be really cheap. Here’s a list of countries I visited: Austria, Belgium, Denmark, Germany, the Netherlands, Northern Ireland, Spain, Sweden, Switzerland.
Working toward a PhD is super hard. The Chateaubriand fellowship helped me be productive and master new skills all the while having some fun along the way.