Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- Linköping University
- NTNU - Norwegian University of Science and Technology
- Newcastle University
- Technical University of Munich
- The University of Manchester
- Bucharest Universty of Economic Studies
- Inria, the French national research institute for the digital sciences
- Iquadrat Informatica SL
- NTNU Norwegian University of Science and Technology
- University of Exeter
- Aalborg Universitet
- Aalborg University
- Centrale Supelec
- Cranfield University
- Delft University of Technology (TU Delft)
- Duke University
- Ecole Centrale de Lyon
- Eindhoven University of Technology (TU/e)
- Fondazione Bruno Kessler
- Fritz Haber Institute of the Max Planck Society, Berlin
- GFZ Helmholtz-Zentrum für Geoforschung
- Ghent University
- IMEC
- Imperial College London
- Imperial College London;
- Instituto de Telecomunicações
- KU LEUVEN
- Leiden University
- Lulea University of Technology
- NVIDIA Denmark
- Nature Careers
- Queensland University of Technology
- Sorbonne Université, CNRS, Inserm
- Tallinn University of Technology
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- University of Adelaide
- University of Birmingham
- University of Bologna
- University of Essex;
- University of Galway
- University of Surrey;
- 32 more »
- « less
-
Field
-
of distributed MIMO, and/or coordinated multi-AP operation (under study in the Wi-Fi 8 standardisation workgroup), using Hardware Description Language on FPGA, based on the open-source openwifi project (https
-
research support staff. They come from different institutions and are distributed across the laboratory's three sites: the main campus, Minatec, and Montbonnot. The laboratory's ambition is to build
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
distribution. The work also aims to improve inference efficiency by reducing dimensionality, reusing computations, and combining multiple measurements. The PhD candidate will develop, test and validate
-
for sensing. Leadership in task involving waveform design and cooperative algorithms. These will include 1) high resolution algorithms 2) distributed sensing compression at the nodes; 3) joint processing
-
(CAITE) whose aim is twofold. First, it aims to bring AI at the edge, by providing scalability and resource efficiency through the development of cooperative, distributed AI algorithms, optimising data
-
of variable distributions [13,14]. Graphic neural networks (GNNs) are new inference methods developed in recent years and are attracting increasing attention due to their efficiency and ability in solving
-
, soil, and plants aid in the collection of real-time data directly from the ground. Based on these historical data predictive machine learning (ML) algorithms that can alert even before a problem occurs
-
Communication Solutions, IoT verticals, Unmanned Aerial Vehicles, Integrated Satellite-Space-Terrestrial Networks, Quantum Communications and Key Distribution, Spectrum Management and Coexistence, Tactile
-
algorithms to guarantee the reliable operation of semiconductor machines, together with a highly innovative industrial partner in the Brainport region. If all these sounds fascinating, then this PhD position
-
correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid