Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
on neural networks whose parameters are trained on simulations (SBI — Simulation-Based Inference). The recruited person will work within the ZTF, LSST/DESC and Lazuli collaborations to implement cosmological
-
the REFFRACTEUR European Doctoral Network. The 36-month doctoral programme will be organised as follows: Months 1–9 (9 months): the doctoral candidate will work primarily at the IMERYS research site in Lyon, France
-
to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6303-JERROS-002/Default.aspx Requirements Research FieldEngineeringEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD or equivalent
-
modified under the influence of an external electric field (E). Antiferroelectric materials, on the other hand, have an antipolar dipolar structure corresponding to a net polarization of zero and undergo a
-
identification of exchange networks from local to extra-regional scales. The doctoral candidate is expected to conduct metallographic examinations and chemical characterizations (primarily SEM-EDS and LA-ICP-MS
-
Analysis and Architecture (LAAS) within the MechaBioFluidics team, which has extensive expertise in microfluidics and microfabrication (a technology platform of the national ReNaTech network), both located
-
, information and communication sciences, anthropology, history, and geography. This teamwork will be carried out within the framework of INRAE's national viability network. The successful candidate will benefit
-
, network-based analysis, unsupervised learning and interpretable AI. The project leaves room for methodological exploration while remaining closely connected to biological interpretation, experimental
-
this PhD project is part of the REFFRACTEUR European Doctoral Network, the 36-month doctoral programme will be organised as follows: Months 1–9 (9 months): the doctoral candidate will work at SAFRAN's
-
structure and hydrogen migration pathways. Integrated Approach and Modeling Framework The project is based on a multiscale observation strategy that combines dense nodal seismic networks, distributed acoustic