Research Associate - AI-based Process Monitoring

About the role

The School of Mechanical & Aerospace Engineering (MAE) at NTU is looking for a Research Associate to develop novel AI methods for process monitoring in laser-based metal additive manufacturing. The role focuses on thermal field modelling, multi-physics numerical simulations, machine learning and process parameter optimisation, using data-efficient AI to predict process anomalies and material defects and improve part quality, process stability and sustainability.

Key responsibilities

• Work on a cross-disciplinary project at the intersection of fluid mechanics, numerical simulation, design optimisation and machine learning
• Collect thermal data from the metal additive manufacturing process
• Develop cost-efficient and data-efficient AI models
• Perform process anomaly and material defect detection
• Implement real-time process monitoring for layer-wise printing
• Collaborate with internal and external stakeholders on energy systems
• Maintain lab or equipment and supplies, including procurement and liaison with suppliers
• Produce high-quality reports and documents consolidating research findings
• Mentor thesis-based undergraduate and master's students
• Assist in proposal writing

Required profile

• Master's degree or above in Mechanical, Structural, Energy, Industrial Engineering, Machine Learning or a related field
• Expertise in laser-based metal additive manufacturing
• Expertise in data-driven and AI/machine learning research
• Strong understanding of research methodology, data analysis and statistical techniques
• Ability to work independently and collaboratively, with strong written and verbal communication skills
• Ability to produce technical content for publication and present to diverse audiences
• Publication track record is an advantage

Required skills

• Proficiency in basic programming languages such as C++, Python and/or Matlab
• Analytical and problem-solving skills, attention to detail and ethical standards in research