Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Ecole Centrale de Lyon
- UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE
- Inria, the French national research institute for the digital sciences
- Nantes Université
- Aix-Marseille Université
- BRGM
- CNRS UMR6614 CORIA
- ENVT INRAE
- European Synchrotron Radiation Facility
- INRIA
- INSA Rennes
- Institut National des Sciences Appliquées de Lyon
- Institut Pasteur
- LEM3
- Sorbonne University, IMPMC-UMR 7590
- Universite de Montpellier
- Université de Poitiers
- cnrs
- 9 more »
- « less
-
Field
-
30 kHz by a burst laser source combined to two Optical Parametric Oscillators (OPOs) [7] applied on H2/air flame. The optimization of OH and NO excitation strategies and the quantification
-
signals. Excessive sound can rupture tip links, silencing the hair cell. In vitro studies show that tip links can re grow within 24–48 hours[4,5], but little is known about how this repair process behaves
-
Description This PhD project aims to develop advanced software solutions for cryo-electron microscopy (cryo-EM) data analysis, modeling conformational heterogeneity, and identifying optimal binding candidates
-
, glycogen and future gonads of males and females. The results will allow for a better understanding of the reproductive processes in this insect within the fundamental context of sexual selection. It will
-
for the turbomachinery design optimization process conducted by a parallel PhD student at LMFA. The numerical solver involved is ProLB. It is an innovative Computational Fluid Dynamics (CFD) software solution developed
-
innovative projects that have a major impact on society. Context and contributions of the position: Understanding subsurface fluid flow is crucial for optimizing geothermal systems and mitigating risks such as
-
processes. The targeted configuration concerns Görtler vortices --- pairs of longitudinal counter-rotating vortices in boundary layers over concave walls --- structures relevant for aerospace and energy
-
promising technology for producing large and complex metal component. Although its potential has been widely demonstrated, significant challenges remain in optimizing the process to ensure the quality
-
for cryo-electron microscopy (cryo-EM) data analysis, modeling conformational heterogeneity, and identifying optimal binding candidates, by integrating image analysis and docking across multiple structural
-
meters. These instruments produce large amounts of data that require several processing steps before the relevant physical variables are obtained. Typically, machine learning methods are used to optimize