Aims
Neuromatch Academy aims to introduce traditional and emerging tools of computational neuroscience and deep learning to trainees with an emphasis on theory and model building. Our student population ranges from undergraduates to faculty in academic settings and also includes industry professionals. Students have a diversity of backgrounds including experimental and computational neuroscience and machine learning. In addition to teaching the technical details of computational methods, we also provide a curriculum centered on modern neuroscience concepts taught by leading professors along with explicit instruction on how and why to apply models. For a detailed description of the content we cover in computational neuroscience, see our syllabus from last year's course.
International and Interactive
Students participating on our Interactive track will be placed into TA-led pods using the neuromatch algorithm, which matches students with common interests who are in the same timezone. Students will receive personalized support as they work through hands-on coding tutorials together over video chat. For more information about last year's course, visit our NMA2020 School Structure page.
Group Projects
Small groups of 3-5 students will work together on projects that put the concepts of the school into action. These projects will utilize large publicly-available datasets. Students who are interested in pursuing their projects further will produce virtual presentations of their work at the end of the school and may be invited to participate in a special issue of the NBDT journal.
Extra-Curricular Opportunities
In order to capture all aspects of traditional summer schools, Interactive students will also be offered mentoring from professors in the field, professional development seminars, career panels and opportunities to virtually socialize with their fellow students.
Free, Flexible Learning
Students who do not have the time to commit to the Interactive track can participate as Observers. Observers get access to all lectures and tutorials but do not join TA pods or group projects. (In fact the lectures and tutorials are posted on Youtube and Github for anyone to access). in 2020, Observers could interact with fellow students through an INCF-hosted discussion forum and could signed up to be matched with up to 5 other observers that share their research interests using the neuromatch algorithm, for extra networking opportunities. We are hoping to provide the same opportunities in 2021. In addition, all of our course materials will remain open to the public after the school and freely available.
