Research Fellow – Physics‑Informed AI & Computational Materials Mechanics

About the role

The School of Mechanical & Aerospace Engineering at NTU seeks a Research Fellow to develop physics‑informed AI models for discovering damage‑tolerant structural alloys for extreme environments. The role bridges AI, computational mechanics, and experimental data to predict deformation and fracture behaviour.

Key responsibilities

• Develop physics‑informed AI and surrogate models for predicting deformation and fracture in structural alloys.
• Integrate AI with crystal plasticity finite element and phase‑field simulations.
• Combine simulation and experimental data for model training, calibration and validation.
• Apply inverse design and optimisation to identify damage‑tolerant microstructures and guide additive manufacturing processes.
• Collaborate with experimental researchers to interpret mechanisms and validate model predictions.
• Assess model accuracy, uncertainty and applicability across microstructures and environmental conditions.
• Publish research findings, contribute to project reports and mentor students.

Required profile

• PhD in Materials Science and Engineering, Mechanical Engineering, Computational Mechanics or a closely related field.
• Strong knowledge of computational mechanics or computational materials science with hands‑on experience in crystal plasticity finite element modelling and/or phase‑field simulations.
• Experience developing AI or machine‑learning models for physics‑based scientific or engineering applications.
• Proficiency in Python and scientific computing frameworks such as PyTorch or TensorFlow.
• Good understanding of microstructure‑property relationships and deformation mechanisms; fracture mechanics knowledge is desirable.

Required skills

• Python programming
• PyTorch or TensorFlow
• Crystal plasticity finite element modelling
• Phase‑field simulations