-
range of computer vision tasks. Their strong representational capacity, however, comes at the price of significantly higher computational complexity and memory requirements. This poses a major challenge
-
to collaboratively train machine learning models without sharing their data. Instead, clients exchange local model updates with a central server, which uses them to improve a global model. While this paradigm enhances
-
efficiency exceeding 15%, based on GaN technology. Methods / Means Analytical, Matlab, ADS, Python Applicant Profile You are working toward a master of research or engineering degree in electrical engineering
-
responsible to develop and test the new software in collaboration with experts of genomics at Joliot and of computer science at MdS. Your mission will include: Discussions and set-up of the physical models
-
for process-local loose coupling in high-performance simulation codes. PDI supports the modularization of codes by inter-mediating data exchange between the main simulation code and independent modules (plugins
-
We are looking for a candidate with a Master's degree, Engineer's degree or PhD in computer science, junior or senior, to join a team responsible for the packaging, deployment, and testing