Sort by
Refine Your Search
-
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
-
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
-
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
-
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
-
Microelectronics teams, the PhD student will be supervised and helped. He/She will access, after training, the IEMN technological platforms. He/She will be provided the tools and computer accesses necessary
-
. Experimental characterization of Hall effect thrusters using combination of diagnostic techniques such as optical emission and absorption, Langmuir probes, etc. enhanced by the application of machine learning
-
, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https://emploi.cnrs.fr/Offres/CDD
-
, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management
-
of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
-
parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large