We are inviting applications for two exciting PhD positions in generative modeling using spiking networks. As part of a highly collaborative team, you will contribute to the development of new mathematical and computational tools for creating realistic models of neural networks.
The project focuses on two main areas: investigating the mathematical relationship between spiking networks and diffusion-based generative models, and exploring the interface between binary spikes and continuous signals. These investigations will lead to significant advancements in speech synthesis and other applications.
To succeed in this role, you should possess a solid foundation in physics, mathematics, or engineering, complemented by skills in programming, machine learning, and statistics. A good understanding of differential equations is also essential.
The positions offer a unique combination of academic excellence and real-world impact. Successful candidates will have access to state-of-the-art facilities and mentorship from experienced researchers.