Research Fellow: Physics-Informed AI for Durable Alloys

ntu; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

NTU is seeking a Research Fellow in Singapore to develop physics-informed AI models for discovering damage-tolerant structural alloys for extreme environments. The role combines AI with crystal plasticity FEM and phase-field simulations, training on experimental data to predict deformation and fracture behavior.

You will collaborate with experimental researchers to interpret mechanisms, validate model predictions and assess uncertainty across microstructures and environments.

Qualifications

• PhD in Materials Science and Engineering, Mechanical Engineering, Computational Mechanics, or a closely related field.
• Strong knowledge of computational mechanics or materials science with hands-on modelling experience.
• Experience in AI/ML for physics-based applications and data integration.

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 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.

Skills

Python

AI/ML experience

FEM modeling

Phase-field simulations

Education

PhD in Materials Science and Engineering, Mechanical Engineering, Computational Mechanics, or related field

Tools

PyTorch

TensorFlow

Crystal plasticity FEM

Phase-field

Job description

NTU is seeking a Research Fellow in Singapore to develop physics-informed AI models for discovering damage-tolerant structural alloys for extreme environments. The role combines AI with crystal plasticity FEM and phase-field simulations, training on experimental data to predict deformation and fracture behavior.

You will collaborate with experimental researchers to interpret mechanisms, validate model predictions and assess uncertainty across microstructures and environments.