Learning Partial Differential Equations with fMRI Data

Closed
EL
Careers & Experience Team
(348)
3
Preferred learners
  • Edmonton, Alberta, Canada
  • Academic experience or paid work
Categories
Data Creative writing Data science Scientific research
Skills
feature films partial differential equation data analysis
Project scope
What is the main goal for this project?

In this project, we apply an appropriate data-driven method to derive the potential partial differential equation model hidden in an fMRI dataset collected by Visconti di Oleggio Castello, Matteo et al. (2020). This dataset records the responses of 25 subjects who watched part of the feature film "The Grand Budapest Hotel" by Wes Anderson.

What tasks will learners need to complete to achieve the project goal?

The student completed the data analysis during the summer, and we are currently in the process of drafting a paper. The next steps involve the student finalizing the literature review and composing the data analysis section.

How will you support learners in completing the project?

We will establish regular meetings to provide ongoing guidance and feedback. Additionally, we plan to facilitate a conducive work environment by applying for dedicated office space for the student, fostering an environment conducive to collaboration and focused project work.

About the company

The Department of Mathematics and Statistics provides a vibrant and supportive home base for students who want to study mathematics and statistics. Our growing department is home to excellent scholars and has a deep commitment to student success, whether taking math as a requirement or as a pursuit of passion. Our faculty members are dedicated to providing an education that emphasizes the knowledge and broad analytical skills that are valuable in today’s world.

Beyond the classroom, our department organizes Torus Talks, a regular presentation series where faculty and students share insights into the uses and versatility of mathematics and statistics, and a Math Help Centre, where students can access additional support in mastering their course work.