Research Associate: AI for Laser Metal AM

Nanyang Technological University; Singapore; On-site; SGD 60,000 - 75,000; Full time

Job summary

NTU Singapore's School of Mechanical & Aerospace Engineering seeks 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 simulations, machine learning and parameter optimization.

The candidate will collect thermal data, build data-efficient AI models, detect anomalies, and implement real-time monitoring while collaborating with colleagues and mentors to advance high-quality

Qualifications

• Master's degree or higher in mechanical/energy/industrial engineering or ML.
• Experience with laser-based metal additive manufacturing.
• Proficiency in programming (Python/C++/MATLAB) and data analysis.
• Strong communication and ability to publish research results.

Responsibilities

• Collect thermal data from metal additive manufacturing process.
• Develop cost-efficient and data-efficient AI models.
• Perform process anomaly and material defects detection.
• Implement real-time process monitoring for layer-wise printing.
• Collaborate with internal and external stakeholders on energy systems.
• Maintain lab/equipment and liaise with suppliers.
• Produce high-quality reports and documents with research findings.
• Mentor thesis-based undergraduate and master students.
• Assist in proposal writings.

Skills

AI research

Python

C++

Machine learning

Data analysis

Education

Master's degree or above in relevant fields

Tools

Laser-based AM

MATLAB

Python

C++

Job description

NTU Singapore's School of Mechanical & Aerospace Engineering seeks 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 simulations, machine learning and parameter optimization.

The candidate will collect thermal data, build data-efficient AI models, detect anomalies, and implement real-time monitoring while collaborating with colleagues and mentors to advance high-quality