Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Grenoble INP - Institute of Engineering
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Universite de Montpellier
- CEA
- European Synchrotron Radiation Facility
- French National Institute for Health Research (INSERM)
- IMT Nord Europe
- INSA Rouen Normandie
- Sorbonne Université
- Télécom Paris
- University of Luxembourg
- Université Côte d'Azur
- Université Savoie Mont Blanc
- Université de Bordeaux / University of Bordeaux
- Université de Limoges
- Université de Reims Champagne Ardenne
- 8 more »
- « less
-
Field
-
optimization models for electric vehicle fleet charging planning. Activities: • Apply operations research methods (linear and mixed-integer programming, dynamic optimization, stochastic optimization) • Integrate
-
, or optimization**, connected to **artificial intelligence** and the research of **Antonin Chambolle** and his collaborators at CEREMADE. The position is a research position. The candidate will interact mainly with
-
investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
-
to develop, optimize and apply advanced mass spectrometry approaches for the structural and molecular characterization of ARDCs, and to analyze and interpret the resulting data. - Develop and optimize mass
-
with national quantum strategies, such as Canada's National Quantum Strategy. The recruited candidate will participate in a Franco-Canadian collaboration focused on the study and optimization
-
for developing and optimizing plasma-based functionalization processes for ferrimagnetic nanoparticles. The successful candidate will be responsible for investigating the relationships between plasma parameters
-
journals and presentations at conferences. - Collaboration with interdisciplinary research teams as part of the CERTAINTY project. - Optimization and documentation of modeling configurations for future
-
of studying and optimizing the microstructural and mechanical properties of granular materials bonded by a solidified foam, within the framework of the ANR project BONDINGFOAM. This mission is structured around
-
interaction research. The postdoctoral researcher will contribute to the design and optimization of biomaterials, their biological characterization and the functional validation of the developed models
-
simulate a refined batch of synthetic data. For each batch, the postdoc will estimate Bayes optimal error, an important guide for realistic goals for deep learning. The first batch of synthetic data will be