Sort by
Refine Your Search
-
Listed
-
Employer
- Nature Careers
- CNRS
- CEA
- European Synchrotron Radiation Facility
- FEMTO-ST institute
- Institut Pasteur
- Institut d'Electronique et de Télécommunications de Rennes
- Nantes University
- UNIVERSITE PARIS CITE
- Université Paris-Saclay GS Biosphera - Biologie, Société, Ecologie & Environnement, Ressources, Agriculture & Alimentation
- Université de Bordeaux
- Université de Technologie de Belfort-Montbéliard
- 2 more »
- « less
-
Field
-
Nature Careers | Port Saint Louis du Rhone, Provence Alpes Cote d Azur | France | about 2 months ago
on therapeutic targets. Modeling macromolecular complexes in silico. Environment. The AFMB is located on the Luminy campus of Aix-Marseille University (amU), at the heart of the Calanques National Park . It is
-
within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies
-
minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
-
The IT Project Manager plays a key role in driving digital initiatives within the Department of Medical Informatics (DMI) at the Luxembourg Institute of Health. Operating under the IT Strategy
-
has a wide range of applications in domains focused on monitoring and securing complex systems, including mobility, manufacturing, communication, economics, and environmental science. These domains
-
learning and AI, stochastic modeling and programing or applied mathematics (Laboratoire J.-A. Dieudonné ) and in Computer Science (I3S & Inria ), with expertise in complex data representation and processing
-
Informatics, in press. [MEO18] M. Meo, T. Pambrun, N. Derval, C. Dumas-Pomier, S. Puyo et al., “Noninvasive assessment of atrial fibrillation complexity in relation to ablation characteristics and outcome
-
on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
-
research work will be to devise efficient algorithms for source separation in DAS measurements. Issues such as large data volumes that can exceed 1 To per day and per fiber, instrument noise, complex nature
-
these applications are generating structured, high-dimensional data with non-trivial and intricate geometric properties. These data often display complex relationships and dependencies that go beyond