Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Nature Careers
- Arts et Métiers Institute of Technology (ENSAM)
- Ecole Normale Supérieure
- Ecole polytechnique
- Institut Pasteur
- Universite Grenoble Alpes
- University of Paris-Saclay
- Université Grenoble Alpes
- Université Paris-Saclay (UPS)
- Université Paris-Saclay GS Mathématiques
- Université Savoie Mont Blanc
- École nationale des ponts et chaussées
- 4 more »
- « less
-
Field
-
laboratory team is likewise highly recognized for its research in computer vision and neuro-inspired artificial learning. Both teams have been collaborating for four years on projects at the interface between
-
by exploiting foundational machine-learning potentials such as MACE, SevenNet, or Orb-V3. The predictions will then be progressively refined and verified by DFT and, ultimately, tested experimentally
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
Framework Programme? Not funded by a EU programme Reference Number 2025-09322 Is the Job related to staff position within a Research Infrastructure? No Offer Description Context. This PhD thesis is part of
-
for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as
-
algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
-
machine learning with the logical reasoning and semantic understanding of symbolic AI (often referred to as material and design informatics) is being developed for the accelerated discovery and development
-
: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
-
technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in
-
-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
-
, engineering, bioinformatics, machine learning, artificial intelligence) to support minimally invasive and targeted preventive and predictive medicine capable of limiting age-related functional disorders