Research Fellow (AI for Materials and Process Development)
Core
Conduct research on AI-enabled discovery and development of advanced functional materials and coating processes using data-driven modelling and experimental validation.
Role type
Research Fellow (AI for Materials and Process Development)
Builds
Scientific machine-learning models and AI-guided experimentation methods for materials and coating processes
Domain
Materials Science / Chemical Engineering / Artificial Intelligence
Deliverable
production ML models
Required skills
Python, predictive modelling, uncertainty-aware learning, AI-guided experimentation, data-driven methods, experimental validation
Preferred skills
materials data experience, manufacturing process data, coating knowledge, functional materials knowledge
Technologies
Python
Responsibilities
Develop AI-guided experimentation methods integrating data, predictive modelling, uncertainty and validation; Build structured materials/process datasets and robust scientific machine-learning models for sparse and noisy data; Design experiment-selection and decision strategies under multiple objectives and engineering constraints; Interpret model and experimental results to derive actionable, transferable materials and process insights (via careerplan.io/jobs/R00020450-research-fellow-ai-for-materials-and-process-development-at-ntu)
Seniority
Mid-Senior, hands-on IC researcher