Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Nature Careers
- CNRS
- Institut Pasteur
- Inria, the French national research institute for the digital sciences
- CEA
- Mediterranean Institute of Oceanography
- The American University of Paris
- Université de Bordeaux / University of Bordeaux
- ;
- Aix-Marseille Université
- American University of Paris;
- CEA-Saclay
- Consortium Virome@tlas
- ESRF - European Synchrotron Radiation Facility
- European Magnetism Association EMA
- European Synchrotron Radiation Facility
- FEMTO-ST institute
- French National Research Institute for Sustainable Development
- Hult
- IMT MINES ALES
- Institut Curie - Research Center
- Institut Neel
- Institut Pasteur de Lille
- Laboratoire d'Astrophysique de Marseille
- Nantes Université
- Toulouse School of Economics
- UNIVERSITE PARIS CITE
- UNIVERSITY OF VIENNA
- University of Montpellier
- Université Côte d'Azur
- Université Paris-Saclay (UPS)
- Université Paris-Saclay GS Mathématiques
- Université d'Orléans
- Université de Bordeaux - Laboratoire IMS
- Université de Caen Normandie
- Université de Montpellier
- Université de Pau et des Pays de l'Adour
- École Normale Supéireure
- École Normale Supérieure
- 29 more »
- « less
-
Field
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 4 days ago
Objective. The goal is therefore to develop explainable mechanisms to 1) clearly inform end users about the different risks of inference, and 2) give the user control what risk is acceptable or not to them
-
selection criterion in some extent. This strongly suggests revisiting the study of these latent variable models with a Bayesian point of view and to understand how this evidence lower bound integrate implicit
-
comprehensive framework for exploring the interactions between viruses, hosts, and the environment at a global scale. This analysis will be inferred from the large amount of data deposited in the Peta-bytes
-
many accomplishments, was one of the early founders of statistical inference and data science. The selected candidate will be located at the new vibrant ENS center for data sciences and participate
-
. - Compilation of a curated catalog of archaeal genomes from public data and newly obtained data within the team. - Orthogroup inference, multi-clade pangenome graphs to detect genes with restricted distributions
-
of several researchers working in the field of inverse problems due to their ability of combining variational inference approaches with the ability of neural networks to learn unknown posterior distributions
-
revisited in light of these new findings. The impact of uncertainties -such as those related to kinetics and radiation- on simulations of spherical flames (typically used experimentally to infer
-
for high-dimensional learning and generative modeling. Research interests span representation learning, statistical inference, privacy, and generative models with applications in physics, audio, vision, and
-
batch effect correction. Single cell and Spatial transcriptomic analysis: Perform clustering, cell-type annotation, trajectory inference, cell-cell communication. Data integration: Apply statistical and
-
experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP