Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- CWI
- Cranfield University
- DAAD
- Monash University
- ;
- ; University of Birmingham
- ; University of Exeter
- ; University of Warwick
- Aalborg University
- Chalmers University of Technology
- Curtin University
- Ecole Polytechnique Federale de Lausanne
- Ghent University
- La Trobe University
- Linköping University
- National Research Council Canada
- Swedish University of Agricultural Sciences
- Technical University of Denmark
- The Max Planck Institute for Neurobiology of Behavior – caesar •
- University of Alaska
- University of Luxembourg
- Vrije Universiteit Brussel
- Østfold University College
- 14 more »
- « less
-
Field
-
portfolio across multiple sectors and disciplines, serve as a key member of the ACEP leadership team, contribute to strategy, operations, and collaboration across programs, lead research teams, build new
-
create a computational tool based on experimental input, simulated data, and machine learning methodology to extract 3D atomic structure information from 2D identical location STEM images. STEM image data
-
use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group
-
point of this project is the opportunity for the successful applicant to work within the Centre for Computational Engineering Sciences, a leading hub for research and education in computational methods
-
Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
-
measurements to the results of existing techniques using backscatter to quantify forest attributes through synthetic aperture radar imaging. The overall project, spanning multiple institutions, aims to produce a
-
skilled human operators must acquire and integrate information from multiple distributed sources (e.g., physical and informational environments) to coordinate cognitively (e.g., decision-making) and
-
organizations and typically informs important decisions in healthcare, governments and finance. Yet, while AI has demonstrated a high impact on applications on text and images, proportional progress on structured
-
microglia is a hallmark of neurodegenerative diseases such as multiple sclerosis (MS) and Alzheimer’s Disease (AD). These lipid-loaded microglia are associated with disease pathology and enhance
-
, healthcare and finance. Yet, while AI has demonstrated a high impact on applications on text and images, proportional progress on tabular data is lacking. With the TRL Lab (Table Representation Learning Lab