AI Scientist, Composite Materials, IMRE

Roles & Responsibilities

We are seeking a highly motivated Research Scientist to join our interdisciplinary team developing next-generation AI-driven materials discovery platforms. The successful candidate will contribute to the integration of experimental materials research, scientific data infrastructure, and artificial intelligence to accelerate the discovery and optimization of advanced materials.

This role offers the opportunity to work closely with experimental scientists, computational researchers, and AI specialists to develop data-driven workflows that enable autonomous materials research. The candidate will contribute to projects spanning materials synthesis and characterization, scientific data management, machine learning, and laboratory workflow automation. Opportunities for scientific publications, intellectual property development, industrial collaborations, and technology translation are also available.

Key Responsibilities

• Design, conduct, and support experimental research on advanced materials, including synthesis, processing and characterization.
• Develop standardized automated experimental protocols and ensure high-quality, reproducible scientific data generation.
• Build, curate, and maintain high-quality materials datasets from experimental, computational, and literature sources.
• Develop automated data processing and analysis workflows to support AI-driven materials discovery.
• Develop Python-based tools and scientific workflows for data collection, preprocessing, visualization, and analysis.
• Collaborate with researchers to integrate laboratory instruments, databases, and computational workflows into a unified research platform.
• Apply machine learning, statistical analysis, and data-driven approaches to identify structure-property-processing relationships and accelerate materials optimization.
• Support the development of AI-assisted research tools, including scientific databases, knowledge management systems, and autonomous experimentation workflows.
• Work collaboratively with multidisciplinary teams across materials science, chemistry, computer science, automation, and data science.

Requirements

• PhD in Materials Science and Engineering, Chemistry, Chemical Engineering, Computational Materials Science, Computer Science, Electrical Engineering or a related discipline.
• Experience with experimental techniques relevant to advanced materials research.
• Programming experience in Python for scientific computing, data analysis, or workflow development.
• Familiarity with scientific programming libraries such as PyTorch, NumPy, pandas, SciPy, matplotlib, or similar.
• Experience developing data analysis pipelines, automation scripts, or scientific software is advantageous.
• Exposure to machine learning, artificial intelligence, data science, or materials informatics is highly desirable.
• Familiarity with SQL, databases, data management, version control (Git), Linux, or high-performance computing environments is advantageous.
• Strong analytical and problem-solving skills with the ability to work independently and collaboratively.
• Demonstrated ability to contribute to multidisciplinary research projects.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

Tell employers what skills you have

Library Science
Liaise with laboratories
Materials Science
scientific software
Materials and Manufacturing Engineering
Artificial Intelligence
Research Tools
Chemistry
Materials Engineering
Python
High Performance Computing
Materials Testing
Test Protocols
Materials Technology
Data Analysis Tools
Able To Work Independently