Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Denmark
- Forschungszentrum Jülich
- DAAD
- Nature Careers
- Cranfield University
- Technical University of Munich
- CNRS
- University of Luxembourg
- Delft University of Technology (TU Delft)
- Susquehanna International Group
- Leiden University
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- NTNU - Norwegian University of Science and Technology
- AALTO UNIVERSITY
- Linköping University
- Tallinn University of Technology
- University of Southern Denmark
- Delft University of Technology (TU Delft); Delft
- Leibniz
- Uppsala universitet
- ; City St George’s, University of London
- ETH Zürich
- Fraunhofer-Gesellschaft
- Humboldt-Stiftung Foundation
- Maastricht University (UM)
- NTNU Norwegian University of Science and Technology
- Radboud University
- ; Swansea University
- Curtin University
- Duke University
- KU LEUVEN
- La Trobe University
- Leiden University; Leiden
- UNIVERSITY OF HELSINKI
- Umeå University
- University of Amsterdam (UvA)
- University of Basel
- University of Bergen
- University of East Anglia
- University of Nottingham
- University of Sheffield
- University of Southern Queensland
- VIB
- Vrije Universiteit Brussel
- AMOLF
- Aalborg University
- Aarhus University
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Carnegie Mellon University
- Delft University of Technology (TU Delft); today published
- Eindhoven University of Technology (TU/e); Eindhoven
- Empa
- GFZ Helmholtz Centre for Geosciences
- Ghent University
- Graz University of Technology
- Heidelberg University
- ISCTE - Instituto Universitário de Lisboa
- KINGS COLLEGE LONDON
- Leiden University; today published
- Lulea University of Technology
- Maastricht University (UM); Maastricht
- Maastricht University (UM); yesterday published
- Monash University
- Murdoch University
- Mälardalen University
- New York University
- Norwegian University of Life Sciences (NMBU)
- The Ohio State University
- UNIVERSIDAD POLITECNICA DE MADRID
- Umeå universitet
- Universite de Moncton
- University of Adelaide
- University of Amsterdam (UvA); Amsterdam
- University of Amsterdam (UvA); yesterday published
- University of Antwerp
- University of Bristol
- University of Groningen
- University of Nottingham;
- University of Sheffield;
- University of Surrey
- University of Twente (UT)
- Université Laval
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
- ;
- ; Coventry University Group
- ; The University of Manchester
- ; University of Exeter
- Abertay University
- Academic Europe
- Agency for Management of University and Research Grants (AGAUR)
- Agricultural university - Plovdiv, Bulgaria
- Ariel University
- Arts et Métiers Institute of Technology (ENSAM)
- BARCELONA SUPERCOMPUTING CENTER
- Brookhaven Lab
- Brookhaven National Laboratory
- CISPA Helmholtz Center for Information Security
- 90 more »
- « less
-
Field
-
develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
-
postdoctoral researchers, supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because
-
of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
-
for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
-
external partners. Topics of particular interest include the novel development and application of machine learning models--such as large language models, multi-modal foundation models, agentic AI, embodied
-
repaired, reused, or discarded requires sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models
-
) and satellite platforms, and surface energy balance models will be used to obtain evapotranspiration (ET); computer vision and machine learning techniques will also be used to identify and count fruits
-
that are transforming many sectors today through language models, recommendation systems and advanced technologies. However, modern machine learning models, such as neural networks and ensemble models, remain largely
-
on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage data collected from various sources, such as
-
AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
will train machine learning models to identify and assess internal defects with greater accuracy and speed than traditional methods. The results will support predictive maintenance, reduce inspection