AI-Driven Materials & Coatings Research Fellow

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

NTI-NTU Corporate Laboratory is seeking a Research Fellow to advance AI-enabled discovery and development of advanced functional materials and coating processes. You will focus on data-driven modelling, uncertainty-aware learning and rigorous experimental validation, collaborating with NTU and Nanofilm teams.

The role requires a PhD in a relevant field, strong ML/DS skills, and the ability to work across multidisciplinary teams to translate research into actionable insights and publications.

Qualifications

• PhD in CS, AI, Data Science, Materials Science/Engineering or related field.
• Strong ML/DS background with hands-on Python.
• Experience with predictive or uncertainty-aware modelling and AI-guided experimentation.
• Experience with materials/manufacturing data is advantageous.
• Proven research output through publications, patents or software.

Responsibilities

• Develop AI-guided experimentation methods integrating data, predictive modelling, uncertainty and validation.
• Build structured materials/process datasets and robust ML models for sparse/noisy data.
• Design experiment-selection and decision strategies under multiple objectives and engineering constraints.
• Interpret model and experimental results to derive actionable materials/process insights.
• Collaborate with multidisciplinary teams and communicate findings through reports/publications.

Skills

Machine learning

Data science

Python

Uncertainty-aware modelling

AI-guided experimentation

Research

Education

PhD in CS/AI/DS/Materials/Engineering

Tools

Python

Job description

NTI-NTU Corporate Laboratory is seeking a Research Fellow to advance AI-enabled discovery and development of advanced functional materials and coating processes. You will focus on data-driven modelling, uncertainty-aware learning and rigorous experimental validation, collaborating with NTU and Nanofilm teams.

The role requires a PhD in a relevant field, strong ML/DS skills, and the ability to work across multidisciplinary teams to translate research into actionable insights and publications.