Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Arts et Métiers Institute of Technology (ENSAM)
- Ecole polytechnique
- Grenoble INP - Institute of Engineering
- IFP Energies nouvelles (IFPEN)
- IMT Atlantique
- Inria, the French national research institute for the digital sciences
- Nature Careers
- Universite Grenoble Alpes
- Université Savoie Mont Blanc
- École nationale des ponts et chaussées
- 1 more »
- « less
-
Field
-
24 Nov 2025 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering Researcher Profile Other Profession Positions PhD Positions
-
Paris PSL Geosciences Center in Fontainebleau) as well as from the proximity to students working on related topics (e.g., machine learning and experimentation using micromodels). The advances enabled by
-
simulations, optimisation, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https
-
] Cross, E. J., Gibson, S. J., Jones, M. R., Pitchforth, D. J., Zhang, S., & Rogers, T. J. (2021). Physics-informed machine learning for structural health monitoring. Structural health monitoring based
-
knowledge of multi-objective problems. Master students or Engineers in the field of Process Systems Engineering are strongly encouraged to apply. Knowledge of machine learning algorithms, energy markets and
-
will build on recent advances in machine learning for dynamical systems to extract meaningful representations of complex flame dynamics, construct prognostic ROMs, and perform data assimilation
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
advanced seismic methods (including array processing, machine learning, and potentially distributed acoustic sensing) to develop novel approaches for monitoring unsteady and non-uniform flood flows across
-
frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data
-
this goal, it is paramount to characterize the added value of using machine learning in estimating and decoding quantum errors occurring in coded quantum systems. Research program: The PhD student will first