Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- ;
- Carnegie Mellon University
- KINGS COLLEGE LONDON
- Susquehanna International Group
- Technical University of Munich
- Universite de Moncton
- CNRS
- Heraeus Covantics
- Imperial College London
- Leibniz
- McGill University
- Nature Careers
- The University of Chicago
- University of Cambridge;
- University of Luxembourg
- University of Minnesota
- University of Utah
- 7 more »
- « less
-
Field
-
adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
-
well as decentralized machine learning algorithms for large-scale clouds with dynamique parameters. -- Conception of machine learning algorithmes for resource allocation -- Numerical experiments -- Drafting research
-
the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
-
, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
-
from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
-
Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
-
) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
-
strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
-
capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
-
(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution