Sort by
Refine Your Search
-
feeds Scaling analog in-memory computing towards large generative AI models H/F 192 / 778 vacancy Vacancy details Position description Category Micro and nano technologies Contract Internship Job title
-
; PyTorch; parallel and GPU computing Applicant Profile The internship is intended for a final-year Master’s student or engineering student specialising in applied mathematics, signal processing or
-
Computing Devices at CEA-Leti in Grenoble, you will contribute to the development of Bayesian learning methods suited to resistive memories (ReRAM). You will build on the team’s previous work, which
-
and sufficient. Assigning meaning to prototypes is however a time-consuming task, as the various models tend to learn prototypes that do not carry sufficiently high-level meaning. A parallel line of
-
, parallel research axes: pushing model accuracy on systems of several thousand atoms with an IWAE architecture; equipping it with the ability to quantify its own uncertainty — a prerequisite for any use
-
réduire les performances de lecture et de manipulation des qubits. Intégré à un laboratoire de recherche en conception intégrée, et en particulier au sein de l’équipe quantum computing, vous aurez
-
library for computing the elementary matrices associated with near, singular and quasi-singular interactions using advanced integration methods from the literature [2–6], or variants to be defined as
-
. To achieve this, it draws upon its scientific expertise across a wide range of high-tech fields, including artificial intelligence, software design, simulation, cybersecurity, and quantum computing
-
emerging applications requires low–temperature operation of CMOS transistors, such as spatial applications, high performance computing, high energy physics…, with a temperature of operation below 100K
-
équipe et bonne humeur ; Vous avez une première expérience dans une infrastructure IT distribuée et complexe de type HPC ou cloud computing (formation en alternance, expérience professionnelle) ; Vous