PhD - Antwerpen | More than two weeks ago
Neuromorphic systems aim to replicate closely how the brain process information. An event-based camera mimics the biological vision system by asynchronously providing brightness events changes, enabling ultrafast imaging. Compared to traditional cameras, it has a much higher dynamic range, low latency, and high temporal resolution (1 μsec). Moreover, it provides a stream of information in time (event or spikes), naturally combining with how spiking neural networks process information. This combination of bio-inspired vision sensors and spiking neural networks aims to achieve novel and better machine vision paradigms (less data, less processing, lower power, lower latency), deployable in practical applications such as robot vision and autonomy (self-driving, self-flying).
In this PhD project, you will work with event-based sensors on data collected in real-time or from known datasets. You will develop a spike-based neuromorphic solution either on custom imec hardware or based on known available framework running in a computer or embedded system. More specifically, you will focus on the following research questions:
Required background: Engineering science, computer/data science
Type of work: 60% algorithm development, 30% experimental, 10% literature
Supervisor: Steven Latré
Daily advisor: Werner Van Leekwijck, Inton Tsang
The reference code for this position is 2022-067. Mention this reference code on your application form.