79 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" PhD positions at CNRS in France
Sort by
Refine Your Search
-
macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie
-
RESEARCHER (M/F) with the ANR MIJMA (International Migration of Young Africans and Minors to Europe.
). The Laboratory of Economics and Sociology of Work (LEST, http://www.lest.cnrs.fr ) is a joint unit of the CNRS and Aix-Marseille University, specialising in the analysis of work and its various spheres as a
-
PRIME (Projet de recherche inter-instituts multi-équipes) interdisciplinary CNRS programme (http://www.cnrs.fr/mi ). The PhD candidate will be co-supervised by Florence Niedergang (Team « Biology of
-
, C.; Pineau, N.; Perrier, A. J. Chem. Theory Comput. 2020, 16 (11), 7017–7032 https://doi.org/10.1021/acs.jctc.0c00762 . (b) Villegas, O.; Serrano Martínez, M.; Le Bras, L.; Ottochian, A.; Pineau, N
-
congested architectures. For more information, visit my professional website: https://iscr.univ-rennes.fr/daniel-muller Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR6226-DANMUL-005
-
part of the research theme 'Planets and Moons', and will be integrated within the ERC - IceFloods (https://lpg-umr6112.fr/en/erc-icefloods/ ). This thesis will aim to characterize the contribution of ice
-
companies. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7261-AICBEL-049/Default.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research
-
” team. Website: https://cermav.cnrs.fr/en/equipe/physico-chemistry-and-self-assembly-of… Team Leader: R. Borsali The successful candidate will be responsible for synthesizing glycopolymers based
-
the domain of molecular simulation of physico-chemical processes in proteins. The PhD student will have access to the computer cluster of the lab and to national supercomputers of the GENCI. [1] R
-
new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably