Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- Nature Careers
- Empa
- Aalborg University
- Forschungszentrum Jülich
- Technical University of Munich
- University of Luxembourg
- University of Nottingham
- Aalborg Universitet
- Cranfield University
- DAAD
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Helmholtz-Zentrum Hereon
- Inria, the French national research institute for the digital sciences
- Linköping University
- NTNU - Norwegian University of Science and Technology
- University of Amsterdam (UvA)
- University of South-Eastern Norway
- University of Twente
- Utrecht University
- Vrije Universiteit Brussel (VUB)
- BRGM
- CEA
- Centrale Supelec
- ETH Zürich
- Fundació per a la Universitat Oberta de Catalunya
- Grenoble INP - Institute of Engineering
- Helmholtz Zentrum Hereon
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- IFP Energies nouvelles (IFPEN)
- IMDEA Networks Institute
- INRIA
- International PhD Programme (IPP) Mainz
- LEM3
- Loughborough University;
- Monash University
- NTNU Norwegian University of Science and Technology
- Newcastle University
- Newcastle University;
- Northeastern University London
- Oak Ridge National Laboratory
- Oxford Brookes University
- Radboud University
- Tallinn University of Technology
- Technical University of Denmark
- Technische Universität Berlin •
- The Max Planck Institute for Neurobiology of Behavior – caesar •
- Umeå University
- University of Basel
- University of Birmingham;
- University of Bordeaux - France
- University of Cambridge;
- University of Cyprus
- University of Exeter
- University of Greenwich
- University of Göttingen •
- University of Oxford
- University of Twente (UT)
- University of Tübingen
- cnrs
- 51 more »
- « less
-
Field
-
2026 Interviews: TBC (online) Start date: September 2026 Project Title: AI-Enhanced Battery State of Health Estimation Using Ring Probabilistic Logic Neural Networks Director of Studies: Prof Shahab
-
for quantized and pruned neural networks, creation of quantized and pruned demonstration models, reproduction of state of the art, experiments in heterogeneous quantization Depending on expertise
-
the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
-
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
-
more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By
-
11.11.2024, Academic staff In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In the project...
-
for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web page For further details or alternative project arrangements, please contact: alexis.bishop@monash.edu.
-
) relationship with the low-fidelity response. Extensions include nonlinear information fusion with GPs, Bayesian multi-fidelity inference and deep probabilistic surrogates, as well as MF neural networks
-
network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 4 hours ago
(graph neural networks and transformers) The objective is to learn conformational heterogeneity directly from molecular dynamics simulations and to identify and predict allosteric communication pathways