Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Université de Bordeaux / University of Bordeaux
- Grenoble INP - Institute of Engineering
- INSERM
- Université Savoie Mont Blanc
- IMT Atlantique
- INSTITUT MAX VON LAUE - PAUL LANGEVIN
- Institut Jacques Monod, CNRS UMR 7592
- Institut Pasteur
- Nature Careers
- UNIVERSITE D'ORLEANS
- Universite de Montpellier
- Université Paris Cité
- Université de Limoges
- 4 more »
- « less
-
Field
-
. Indeed, the methods currently used rely on optical image databases of various avalanche observations. A deep neural network was trained on this data to enable automatic avalanche detection FIGURE 1 (a) [1
-
neuronal types shapes sensory coding and circuit computation, with a strong emphasis on neocortical cell diversity and synaptic properties. We integrate detailed biophysical work with in vivo circuit-level
-
methodology and instrumentation, as well as in the field of Biomedical Imaging applications. The laboratory has developed many interactions with research teams specialized in the fields of oncology, cardiology
-
following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
-
of colorectal cancer (CRC) using organoid models. The researcher will focus on integrating dynamic mutations, live multiplexed transcriptomic imaging, and proteomic imaging at the cellular level to predict
-
dislocation dynamics (DDD) code from TRIDIS, NUMODIS, or OpenDIS, based on the candidate's programming skills (Fortran, C++, or C). - Validate the DDD-FFT coupling required to optimize calculations
-
well as potential power deposition on accelerator elements and potential damage. •Subsequently perform the benchmarking of the accelerator model from the Bmad code to the Xsuite / RF-Track codes. This work will
-
electrodes using various electron microscopy techniques (e.g. FIB-SEM); (ii) Reconstruction of the 3D structure through image analysis; (iii) Analysis of images from new and aged membrane-electrode assemblies
-
(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team
-
of techniques — organoids, stem cells, omics approaches, and live imaging — to explore principles of cell-fate specification and tissue morphogenesis. We recently moved into newly renovated laboratory