- Statistical analysis of existing databases (experimental and theoretical) - Generation of structure/property predictive models by statistical learning (machine learning) - Molecular simulations of nanoporous materials
The goal of the project is to study the adsorption properties of Metal-Organic Frameworks (MOF) nanoporous materials, based on experimental data and molecular simulations, in order to establish predictive models based on Artificial Intelligence methods.
This work will be carried out within the framework of the national PEPR Diadem project, in the MOFLearning axis (https: // www. cnrs.fr/en/node/6848), in collaboration with Dr. C. Serre (CNRS, ENS/ESPCI, PSL) for the synthesis and characterization, and teams from CEA Marcoule (Dr. D. Meyer et al).
This position is located in a sector covered by the protection of scientific and technical potential (PPST) and therefore requires, in accordance with the regulations, that your arrival be authorized by the competent authority of the MESR.Eligibility criteria
- Molecular simulation - Programming in Python language - Machine learning methodsWeb site for additional job details
https: // emploi.cnrs.fr/Offres/CDD/UMR8247-FRACOU-006/Default.aspxRequired Research Experiences
Chemistry › Physical chemistry
1 - 4
Chemistry › Computational chemistry
1 - 4Offer Requirements
Chemistry: PhD or equivalent
FRENCH: BasicContact Information