Research Assistant (FEM Modeling)

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading university in Singapore seeks a passionate researcher for FEM simulations of composite materials. You will collaborate with peers while independently conducting simulations to produce data for machine learning, supporting cutting-edge research in advanced materials.

Qualifications

• Degree in mechanical engineering or materials science required.
• Solid knowledge and previous experience in FEM essential.
• Strong interest in machine learning, good communication, and autonomy needed.

Responsibilities

• Learn and understand the experimental system.
• Conduct simulations and resolve related issues.
• Generate data from simulations for machine learning.

Skills

FEM

Machine Learning

Communication

Autonomy

Problem-Solving

Education

Degree in Mechanical Engineering

Degree in Materials Science

Job description

We are part of one of the most dynamic university in Asia and in the world, Nanyang Technological University (NTU) Singapore. Our research group focuses on the design and fabrication of composite materials and structures using new additive manufacturing methods. To carry out our research, we work closely with the Singapore 3D printing Center located at NTU.

For more details, please visit our group website: https://www.hortenseleferrand.com/

We are looking for a researcher able to carry FEM simulations of reinforced composites materials using Abaqus. The experimental characterization of samples already exists and should match with the FEM simulations. The researcher should be able to work autonomously on the simulations, while being able to discuss with the other researchers working on the experiments in order to understand the experimental systems. The FEM simulations should look at the temperature and stress-induced deformation of the composites. The need for the simulations is to generate enough data for machine learning.

Key Responsibilities:

• Learn and understand the experimental system
• Conduct the simulations and resolve issues
• Generate data using the simulations
• Collaborate with other researchers on the project

Requirements:

• A degree in mechanical engineering or materials science
• Previous experience and solid knowledge with FEM
• Do FEM of the deformation of composites with temperature
• Verify FEM matches experimental data
• Use FEM to get large amount of data for machine learning
• Excellent learning ability
• Excellent communication ability
• Strong interest in machine learning
• Candidate should be passionate about research, have excellent learning ability and be able to take initiatives and work independently

We regret to inform that only shortlisted candidates will be notified.