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Deep learning accelerated multiscale modeling of flows

12 Octobre 2023

Catégorie : Post-doctorant

Flows in porous media are of great interest for a wide range of applications such as reservoir engineering or
composites manufacturing. For instance, resin transfer molding is a composite manufacturing process where a polymer resin advances in a meter-sized mold containing a reinforcement with micrometer-sized fibers.
Understanding and accurately modeling these flows is essential in order to design and optimize these processes.

 

Flows in porous media are of great interest for a wide range of applications such as reservoir engineering or composites manufacturing. For instance, resin transfer molding is a composite manufacturing process where a polymer resin advances in a meter-sized mold containing a reinforcement with micrometer-sized fibers.
Understanding and accurately modeling these flows is essential in order to design and optimize these processes.

The ANR JCJC MISSA project has started in 2023 and targets the development of cutting-edge numerical models for two-phase flows in porous media.
Within this project involving two research centers of IMT Nord Europe as well as a research group of the National University of Singapore, the postdoctoral fellow will focus on accelerating calculations with deep learning. Recent technologies such as autoencoders and recurrent neural networks will be considered. The postdoctoral fellow will develop a deep learning model that will be integrated in a multiscale finite element code developed by other partners of the MISSA project. Challenging applications to real manufacturing
processes will be addressed.

The postdoctoral research will be supervised by Prof. Shakoor, Itier and Mennesson from IMT Nord Europe.
Participation in teaching activities is possible up to a limit of 64 hours per school year for postdocs who wish to pursue a career in academia. This position offers:

  • A high-level and exciting international research environment in a renowned institution
  • Being part of an international project team with contacts worldwide
  • A thorough scientific education and training on deep learning and its application to fluid mechanics
  • The possibility to participate in local as well as international workshops and conferences

 

 

REQUIRED PROFILE:

  • A PhD degree in computational mechanics, scientific computing, or computer science
  • Strong programming skills, preferably in Python
  • Some skills in machine learning and/or computational fluid mechanics will be an advantage but are not a requirement
  • Distinguished her- or himself with publications in peer-reviewed international journals and/or presentations in renowned international conferences
  • Strong knowledge of either French or English
  • An open-minded attitude

CONDITIONS:
The job is to be filled as to January-July 2024 for a period of 18 months (temporary contract).


INFORMATION AND APPLICATION METHODS:
For any information on the missions, please contact:
SHAKOOR Modesar, Associate Professor, modesar.shakoor@imt-nord-europe.fr ; +33 3 27 71 23 21

More information : https://institutminestelecom.recruitee.com/o/postdoc-position-on-deep-learning-accelerated-multiscale-modeling-of-flows-cdd-18-month-at-imt-nord-europe


DEADLINE DATE FOR SUBMISSIONS: 01/12/2023