Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- European Space Agency
- Technical University of Munich
- Lawrence Berkeley National Laboratory
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- University of Vienna
- CNRS
- ETH Zurich
- Ecole Centrale de Lyon
- Forschungszentrum Jülich
- Harbin Engineering University
- Imperial College London
- NTNU - Norwegian University of Science and Technology
- Nantes Université
- Nature Careers
- Princeton University
- Technical University of Denmark
- The University of British Columbia (UBC)
- UNIVERSITY OF VIENNA
- University of California
- University of North Carolina at Chapel Hill
- University of Oslo
- University of Washington
- Universität Wien
- Vrije Universiteit Brussel
- Wageningen University & Research
- Wageningen University and Research Center
- 16 more »
- « less
-
Field
-
reconstruction algorithms. Inconsistencies can be used to correct the input data, for example to improve attenuation correction. The aim of this postdoc is to correct rigid motion in SPECT reconstruction based
-
control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and towards our
-
wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
-
wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
-
algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
-
or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems
-
. They come in various configurations, from simple, conceptual lumped models to more complex, distributed ones. Their low input data requirements and flexible application make them widely used by water managers
-
, deliberative workshops with potential pilot communities, surveys, and comparative policy review to capture needs and equity concerns, build an operational model of BC’s transmission system, design distributed
-
trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell