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Research Fellow (AI for Materials and Process Development)

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Onsite

Research Fellow (AI for Materials and Process Development)

Ntu Careers

Research Fellow (AI for Materials and Process Development)

Skills

PythonData ScienceAIWorkday

20 days ago

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Important information


Contract type:

Permanent

Location:

Singapore

Work mode:

Onsite

Published on:

7 October 2026

What they need


NTI-NTU Corporate Laboratory is a collaboration between Nanofilm Technologies International Limited ("Nanofilm", "NTI") and Nanyang Technological University ("NTU"), supported by Singapore under RIE2025. The Laboratory brings together NTU's research capabilities and NTI's deep-technology expertise to advance research, innovation and technology commercialisation.

The NTI-NTU Corporate Laboratory is looking for a Research Fellow to conduct research on AI-enabled discovery and development of advanced functional materials and coating processes, with emphasis on data-driven modelling, uncertainty-aware learning and experimental validation.

Key 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.
  • Collaborate with multidisciplinary academic-industry teams and communicate findings through reports and publications.

Requirements:

  • PhD in Computer Science, AI, Data Science, Materials Science/Engineering, Chemical/Mechanical Engineering or a related field.
  • Strong machine-learning/data-science or computational background with hands-on Python skills.
  • Experience with predictive or uncertainty-aware modelling, AI-guided experimentation or related data-driven methods.
  • Experience with materials, manufacturing or experimental process data is advantageous; coating or functional-materials knowledge is a plus.
  • Proven research capability through publications, conference papers, patents, software or comparable outputs.
  • Independent, analytical and proactive, with effective communication, teamwork and multidisciplinary collaboration skills.

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU

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