Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- CNRS
- The University of Arizona
- ;
- Brookhaven Lab
- NEW YORK UNIVERSITY ABU DHABI
- Nature Careers
- Oak Ridge National Laboratory
- University of Kansas
- University of Sydney
- Virginia Tech
- Artois University
- City University London
- Delft University of Technology (TU Delft)
- Durham University
- ETH Zürich
- FUB - Free University of Berlin
- Forschungszentrum Jülich
- Heriot Watt University
- Itä-Suomen yliopisto
- King Abdullah University of Science and Technology
- Old Dominion University Research Fountation
- Stanford University
- The University of Manchester
- The University of Memphis
- UNIVERSITY OF SYDNEY
- University of California, Merced
- University of Exeter
- University of Stavanger
- Łukasiewicz Research Network - Krakow Institute of Technology
- 19 more »
- « less
-
Field
-
, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
-
has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here . Duties & Responsibilities Breeds
-
sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
-
sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
-
14 Oct 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Physics Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
-
. The position involves the development and application of high-fidelity computational fluid dynamics (CFD) methods, theoretical modeling, and data-driven approaches to study turbulence, aero-thermo-acoustics, and
-
of compressible flow regimes, including supersonic and hypersonic flows, as demonstrated by application materials. Familiarity with machine learning or data-driven modeling approaches in fluid dynamics, as
-
progress and high-impact scientific publications in the areas of ultrafast and nonlinear optics. For more information, please send enquiry emails to Prof John Travers (j.travers@hw.ac.uk ). The application
-
Posting Information Posting Number FAE1959 Advertised Title Post-Doctoral Fellow Campus Location Main Campus (Memphis, TN) Position Number L22894 Category Full-Time Faculty Department Mechanical
-
division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume