Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Istituto Nazionale di Fisica Nucleare
- Forschungszentrum Jülich
- Instituto Nacional de Investigação Agrária e Veterinária, I.P.
- Princeton University
- Curtin University
- Midlands Graduate School Doctoral Training Partnership
- National Renewable Energy Laboratory NREL
- Tilburg University
- Universidade de Coimbra
- ;
- Academic Europe
- CSIRO
- Cardiff University;
- East Tennessee State University
- IMCBio graduate school
- Instituto Nacional de Saúde Dr. Ricardo Jorge
- Karlsruhe Institute of Technology
- Karlstad University
- Massey University
- Max Planck Institutes
- Midlands Graduate School Doctoral Training Partnership;
- Newcastle University
- The University of Auckland
- University of Arkansas
- University of Canterbury
- University of Greenwich
- University of Manchester
- University of Minho
- University of Oklahoma
- University of Oxford
- University of Oxford;
- 21 more »
- « less
-
Field
-
No separate application is required for this scholarship, only the application for admission to the University of Cambridge, which must be submitted by the funding deadline specific to your course (please refer to the Postgraduate Course Directory ) If you wish to be considered for this award,...
-
‑space exploration, and on‑line operational optimization of power systems. Your tasks in detail: Become familiar with our previously developed neural network superstructure for learning iterative
-
detection with minimal latency. Combined with efficient signal processing, this approach enhances detection accuracy while optimizing resource use, supporting cybersecurity and sustainability in IIoT networks
-
to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design‑space exploration, and on‑line operational optimization of power systems
-
bacteria; • Application and optimization of molecular methods for bacterial detection and identification (PCR, qPCR, LAMP); • Support in evaluating and validating rapid diagnostic platforms in the lab and
-
prediction Integration of domain decomposition methods into the learning framework to enable efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation
-
efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation of models on patient-specific geometries obtained from MRI data Participation in conferences