Sort by
Refine Your Search
-
Listed
-
Employer
- CNRS
- Institut Curie - Research Center
- Universite de Montpellier
- BRGM
- CEA Grenoble
- Fondation Hôpital Rothschild
- Grenoble INP - Institute of Engineering
- IMT - Institut Mines-Télécom
- IMT Mines Ales
- INSTITUT MAX VON LAUE - PAUL LANGEVIN
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Sorbonne Université
- UNIVERSITE ANGERS
- Université Marie et Louis Pasteur
- Université Paris Cité
- Université côte d'azur
- Université de Bordeaux / University of Bordeaux
- Université de Pau et des Pays de l'Adour
- 9 more »
- « less
-
Field
-
layered semiconductor characterized by an anisotropic crystalstructure and quasi-one-dimensional ribbon-like morphology. Its electronic structure is predicted to host relatively flat bands associated with
-
. Chemistry A European J2022, 28 (20). https://doi.org/10.1002/chem.202104302 . Cortijo M, Valentín-Pérez Á, Rosa P, Daugey N, Buffeteau T, Hillard EA. Resolution, structures, and vibrational circular dichroism
-
of individual ice crystals and grain boundaries. This postdoctoral project aims to leverage these developments to better constrain the origin, structure, and evolution of basal ice beneath the Greenland and
-
heroin self-administration. Analyze synaptic mechanisms using western blot, RT-qPCR, immunohistochemistry, and electrophysiology (in collaboration). Characterize structural adaptations (dendrites, spines
-
selectivity. Mechanistic analysis: understanding charge transfer processes and reaction mechanisms in photocatalysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7314-FRESAU-017
-
quantify the evolution of the thermal structure of the Aquitaine Basin's crust and mantle using the geological record. Geophysical data, the subsidence history of sedimentary basins, and thermal-mechanical
-
approach makes it easier to identify different local optima using sampling mechanisms. In stochastic optimization, distribution estimation algorithms (EDA) are an alternative approach to traditional
-
elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative
-
implement machine learning models dedicated to the prediction, interpretation, and quantitative analysis of Raman vibrational spectra, establishing explicit links between structure, local chemical environment
-
that seeks to link material structure, transformation processes, performance properties (mechanical, thermal, fire resistance, absorption, etc.), and their evolution throughout the product lifecycle