Path 1 Kawader: Research Assistant in the Computational Solid Mechanics Lab – Professor Mobasher’s research group

New York University

Description

The Computational Solid Mechanics laboratory lead by Professor Mostafa Mobasher in the Division of Engineering, New York University Abu Dhabi, seeks to recruit a Research Assistant to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The multidisciplinary project is co-supervised by Professor Tarek Abdoun and Professor Borja Garcia de Soto from the Civil and Urban Engineering Program. The project is a collaboration between multiple research groups and involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models.

Research project

The successful applicant is expected to work and lead multiple research projects aimed at developing machine learning based digital twins for structural and geotechnical systems. The project will involve collaborations with multiple researchers and industrial partners.

The candidate will also work on individualized research projects under the supervision of the faculty during the duration of his/her tenure.

This position is supervised by Dr. Mostafa Mobasher

Qualifications

Required Qualifications

A successful applicant must have a degree in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning model development.

Preferred Qualifications

Experience in the following will be preferred:

  • The development of computational models to represent structural performance using commercial and research software tools
  • The development and validation of neural network models focused on representing the structural response
  • Physical experimental testing for structural and geotechnical applications
  • Data acquisition and processing from monitoring systems
  • Validation of modeling results against experimental and monitoring data
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Confirmed 14 hours ago. Posted 30+ days ago.

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