Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- NTNU - Norwegian University of Science and Technology
- Aalborg University
- Monash University
- University of Amsterdam (UvA)
- Carnegie Mellon University
- University of Nottingham
- Technical University of Munich
- University of Antwerp
- University of Melbourne
- Radboud University
- The University of Manchester
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- University of Exeter
- Harvard University
- University of Warwick;
- The University of Newcastle
- University of Luxembourg
- National Research Council Canada
- Eindhoven University of Technology (TU/e)
- Queensland University of Technology
- Forschungszentrum Jülich
- University of Twente
- Duke University
- Maastricht University (UM)
- Manchester Metropolitan University
- Newcastle University
- Trinity College Dublin
- University of Basel
- University of Cambridge;
- University of Groningen
- University of Tübingen
- University of Warwick
- AALTO UNIVERSITY
- Friedrich Schiller University Jena •
- Umeå University
- University of Bergen
- University of Birmingham
- University of East Anglia
- University of Oslo
- University of Texas at El Paso
- University of Twente (UT)
- Vrije Universiteit Brussel
- Wageningen University & Research
- Amsterdam UMC
- Durham University
- Fraunhofer-Gesellschaft
- KNAW
- National University of Singapore
- Pennsylvania State University
- SciLifeLab
- Swinburne University of Technology
- Technical University of Denmark
- University of Bonn •
- University of Kentucky
- University of Maryland, Baltimore
- University of Miami
- University of Vienna
- Brandenburg University of Technology Cottbus-Senftenberg •
- CNRS
- Curtin University
- Empa
- Hannover Medical School •
- Heidelberg University
- ICN2
- Jane Street Capital
- Justus Liebig University Giessen •
- King's College London;
- Leipzig University •
- Manchester Metropolitan University;
- Max-Delbrück-Centrum für Molekulare Medizin
- Norwegian University of Life Sciences (NMBU)
- Radix Trading LLC
- Rochester Institute of Technology
- UNIVERSITY OF VIENNA
- University Medical Center Utrecht (UMC Utrecht)
- University of Bedfordshire
- University of Copenhagen
- University of Lund
- University of North Texas at Dallas
- ;
- ARCNL
- Aalborg Universitet
- Aarhus University
- BAM Bundesanstalt für Materialforschung und -prüfung
- Bangor University;
- Baylor College of Medicine
- Centrum Wiskunde en Informatica (CWI)
- City St George’s, University of London
- Cranfield University
- DIFFER
- Deutsches Krebsforschungszentrum
- Dresden University of Technology •
- ETH Zürich
- EURAXESS
- Embry-Riddle Aeronautical University
- Erasmus University Rotterdam
- European Magnetism Association EMA
- FAU Erlangen-Nürnberg •
- 90 more »
- « less
-
Field
-
models of regulation and dynamics . Flow- and diffusion-based models of cellular dynamics are expressive enough to map any source to any target state, but they fall short of learning the underlying
-
. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
-
mathematics, machine learning, photonics, and clinical practices in vision. Be part of a multidisciplinary research team spanning science and engineering, psychology, and healthcare. Access state-of-the-art
-
AI hardware beyond traditional computing architectures. Gain a unique combination of skills in mathematics, machine learning, and photonics. Be part of a multidisciplinary research team spanning
-
measurement methods. These procedures target the assessment of steel properties for reuse in a new construction. Besides experimental work in the laboratory, machine learning will be employed to develop
-
a mixture of computational, analytical and machine learning approaches to model the heat transfer to fuels and their physical and chemical behaviour, including changes in chemistry and physical
-
PhD in Computational Simulations of Turbulent Reaction Flows for Clean Energy and Sustainable Propul
machine-learning methods, you will analyze flame-turbulence interactions, pollutant formation, as well as unclosed terms relevant to LES modeling. The analysis involves the fluid dynamic as
-
University, the Communicable Diseases Agency Singapore (CDA), the National Environment Agency Singapore (NEA), the Machine Learning & Global Health Network (MLGH), and wider regional and global partners. Key
-
design and characterise reconstruction methods—both machine-learning-based and traditional—for the bundles of muons that reach the detectors, and apply them to data and simulations to constrain cosmic-ray
-
This exciting opportunity is based within the Power Electronics and Machines Control Research Institute of the Faculty of Engineering at the University of Nottingham which conducts cutting edge