CENTRALE LYON ENISE - Technicien support informatique

Emerging computing technologies – non-volatile and ferroelectric memories, analog and digital in-memory computing, silicon photonics, 3D integration, and heterogeneous chiplets – offer major gains in energy efficiency, latency, bandwidth, and functionality. Their potential…

The question Generating one image with a diffusion model means evaluating a large neural network tens to hundreds of times. That repetition is where the energy goes, and it is part of why data-centre demand is now visible at grid scale: the Lawrence Berkeley National Laboratory…

The rapid expansion of artificial intelligence (AI) applications across cloud and edge environments is driving the need for highly efficient hardware capable of supporting increasingly demanding workloads. Among these, matrix multiplication – particularly General Matrix…

Energy efficiency remains one of the foremost challenges in modern computing, spanning from edge IoT devices to high-performance data centers. Conventional CMOS-based architectures are approaching fundamental physical limits, while the "memory wall" — data transfers between…

Présentation département L’Institut des Nanotechnologies de Lyon (INL) a pour vocation de développer des recherches technologiques multidisciplinaires dans le domaine des micro et nanotechnologies et de leurs applications. Les recherches menées s’étendent des matériaux aux…

PROJECT OVERVIEW We are looking for a highly motivated Postdoctoral Researcher to develop innovative deeplearning models that predict the structure of functional-oxide thin films directly from their growth dynamics. Positioned at the interface between Artificial Intelligence and…