Design a transformer network for the retina

Motivation

We train neural networks to predict responses of retinal ganglion cells and then further use them to gain insights into the retinal circuitry. So far, we mostly build convolutional neural networks that do not reflect the transformer revolution that happened in the field of deep learning.

Project

In this project you could design and build a transformer that is can predict retinal ganglion cell responses and benchmark it against our state-of-the-art models.

Thesis

Within the context of this project, several research questions could be explored: - Is a transformer architecture able to outperform CNNs in predicting neuronal activity of the retina? - How does the attention mechanism change the predictions compared to convolutions?

Contact

To apply please email Michaela Vystrčilová stating your interest in this research and detailing your relevant skills.