177 assistant-and-professor-and-computer-and-science-and-data-"Multiple" positions in France
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
controlled via structural phase transitions or external fields. The successful candidate will develop and apply a range of theoretical and computational methods based on first-principles electronic structure
-
materials to post-mortem gas analysis. This team is completed by data scientists and electronics engineers. A large anhydrous room is available to build Li-ion cell prototypes, as well as to develop any
-
[map ] Subject Area: Analysis Appl Deadline: (posted 2024/11/15, listed until 2025/05/15) Position Description: Position Description This recruitment operation aims to strengthen at Professor level the
-
of the biological bases of normal and pathological behaviors. Required Qualifications: PhD or equivalent experience in neuroscience, computer science, engineering or a related field. Proven experience in
-
material on team science, adapt to LCSES requirements Ensure close collaboration with the LCSES Data Science and Science-Policy Team as well as the Universities Institute of Advance Studies (IAS) Your
-
, 2024 - C. Bouveyron, M. Corneli and G. Marchello, A Deep Dynamic Latent Block Model for the Co-clustering of Zero-Inflated Data Matrices, Journal of Computational and Graphical Statistics, in press, 2024
-
Deep Dynamic Latent Block Model for the Co-clustering of Zero-Inflated Data Matrices, Journal of Computational and Graphical Statistics, in press, 2024 - A. Destere, G. Marchello, D. Merino, N. Ben
-
of the scientific publications • Motivation letter • Letter of recommendation of the thesis supervisor Description of the topic: Optical fiber, in addition to being a means of transmitting information, is also a
-
of the project stands on the fact that activity recording data are collected and integrated in the model from multiple experimental sources, in the hope to exploit the full power of computational modelling to span
-
Leveraging the spatio-temporal coherence of distributed fiber optic sensing data with Machine Learning methods on Riemannian manifolds Apply by sending an email directly to the supervisor