Multi-modal SNN: Neuromorphic computation for various sensor data

IMRA Europe is looking for a CIFRE PhD candidate in the Department of Computer Science, who is working in collaboration with Cote d'Azur University / I3S. The project consists in designing and implementing multi-modal data processing system using Spiking Neural Network (SNN) and neuromorphic hardware.
We are a research institute developing cutting-edge technology using AI mainly in automotive domain. Our stakeholder, AISIN Corporation, is a large car parts and system supplier targeting system development using AI and various sensor data for intelligent applications. To achieve this, we are focusing on the SNN to utilize its asynchronous processing and low energy consumption to develop applications with various sensors installed on Electric Vehicle (EV), personal mobility for security, on small robots for factory inspection purpose, and more.

The main activities of the project are listed as follows:

• Handle data of various sensor data, which are taken at same time
• Design SNN architecture and train it for solving issues and achieving target application
• Implement designed SNN on neuromorphic hardware
• Publish research results as academic papers in journals and conferences, patents

IMRA Europe (www.imra.eu) is a private research laboratory created in 1986 in Sophia Antipolis (France). The R&D activities of the Department of Computer Science are focused on system development for automotive industry, such as vision system (object detection/recognition on various sensor data), motor control, factory data analysis using AI.

The Computer Science, Signals and Systems laboratory of Sophia Antipolis (i3S), federates research in information and communication sciences and technologies. With nearly 300 people, teacher-researchers, CNRS and Inria researchers, administrative and technical staff, doctoral students and trainees, it is one of the largest public laboratories on the Côte d'Azur and was one of the first to be established in the Sophia Antipolis technology park.

• Master’s degree in computer science
• Experience deep learning (deep neural network) and its development.
• Track record of scientific publications and conference presentations.
• Excellent communication and collaboration skills.