jobs in NANYANG TECHNOLOGICAL UNIVERSITY

全职 Research Fellow (AI for Materials and Process Development) 工作, 薪水 up to SGD 6,000, NANYANG TECHNOLOGICAL UNIVERSITY West Region (Singapore) 公司招聘中 - Ricebowl

Research Fellow (AI for Materials and Process Development)

NANYANG TECHNOLOGICAL UNIVERSITY

West Region (Singapore)

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工作地点

  • 50 NANYANG AVENUE West Region (Singapore) Singapore

职位描述

岗位职责

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.

Job 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.

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