Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Nature Careers
- Inria, the French national research institute for the digital sciences
- Grenoble INP - Institute of Engineering
- Institut Pasteur
- Université Paris-Saclay (UPS)
- Arts et Métiers Institute of Technology (ENSAM)
- CEA
- Centre de Mise en Forme des Matériaux (CEMEF)
- Institut de chimie des milieux et matériaux de Poitiers - Equipe SAMCat
- University of Paris-Saclay
- University of Reims Champagne-Ardenne (URCA)
- Université Paris-Saclay GS Mathématiques
- Université de Bordeaux / University of Bordeaux
- 4 more »
- « less
-
Field
-
innovations, OCTO Technology and the PIMM laboratory at ENSAM are jointly sponsoring this PhD thesis. The research will focus on the application of Physics-Informed Machine Learning (PIML) and Physics-Informed
-
The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
-
-researchers, experimentalists, and theoreticians, and its research activity is supported by around sixty engineers, technicians, and administrative staff. The laboratory welcomes a large number of undergraduate
-
be highly interdisciplinary. Two different profiles are possible for this position: either a profile in engineering sciences or biomedical physics, with a strong desire to learn about microbiology
-
27 Aug 2025 Job Information Organisation/Company CNRS Department Institut d'Electronique et des Systèmes Research Field Engineering Physics Technology Researcher Profile First Stage Researcher (R1
-
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
-
29 Aug 2025 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering Researcher Profile Other Profession Positions PhD Positions
-
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