Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- AIT Austrian Institute of Technology
- Universidad Politécnica de Madrid
- DAAD
- Ghent University
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Helmholtz-Zentrum Hereon
- KU LEUVEN
- National Renewable Energy Laboratory NREL
- University of California
- University of California Los Angeles
- University of Copenhagen
- University of New Hampshire – Main Campus
- University of Southern Denmark
- 3 more »
- « less
-
Field
-
by: Developing specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in
-
focus on a variety of key technologies like Distributed IT Systems, Internet of Things, IoT, Cybersecurity, Data Science, Artificial Intelligence (AI), Blockchain Technologies, Quantum & Photonic
-
focus on a variety of key technologies like Distributed IT Systems, Internet of Things, IoT, Cybersecurity, Data Science, Artificial Intelligence (AI), Blockchain Technologies, Quantum & Photonic
-
Description Distribution estimation algorithms for abductive inference (total or partial) in dynamic domains. Structural learning of dynamic Bayesian networks with discrete and continuous variables (parametric
-
Development, implementation and experimentation of distribution estimation algorithms in dynamic optimization problems. Where to apply E-mail lauragveiga@fi.upm.es Requirements Research FieldComputer science
-
in the body. However, clinical PET imaging has so far been largely limited to imaging the distribution of a single radiotracer per scan. In collaboration with the Forschungszentrum Jülich, the PET
-
conditions are caused, transmitted, and prevented, as well as how they are distributed throughout the population. Such information plays a critical role in guiding policies and other evidence-based strategies
-
Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 days ago
the body. However, clinical PET imaging has so far been largely limited to imaging the distribution of a single radiotracer per scan. In collaboration with the Forschungszentrum Jülich, the PET department
-
, applied optimisation, embedded programming. Objectives: Feature extraction and distributed algorithms to localise any wireless transmitter in mobile environments that does not collaborate (passive
-
, transmitted, and prevented, as well as how they are distributed throughout the population. Such information plays a critical role in guiding policies and other evidence-based strategies to promote health and