AI-Driven Materials Modelling Scientist

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 140,000 - 190,000; Full time

Job summary

A*STAR IAIC invites two new Research Scientists to advance AI-driven materials modelling and discovery. You will design MLIPs, run DFT workflows, and build scalable high-throughput pipelines to explore alloys, semiconductors, and thermal materials.

You will collaborate with computational scientists and AI researchers, publish in journals, and contribute to open-source software underpinning the workflow. Strong independence and teamwork are essential.

Qualifications

• PhD in Materials Science, Physics, Chemistry, or a related discipline.
• Strong background in atomistic materials modelling, computational thermodynamics, or condensed-matter theory.
• Hands-on experience with plane-wave DFT calculations using packages (e.g. VASP, Quantum ESPRESSO).
• Hands-on experience developing, training, fine-tuning, and applying MLIPs or other atomistic ML models (e.g. M3GNet, TensorNet, MACE, GRACE).
• Experience with high-throughput materials workflows and provenance tracking.

Responsibilities

• Develop and apply foundation potentials and MLIPs to predict phase stability and thermal properties.
• Design and execute high-throughput screening workflows for multiple material properties.
• Perform plane-wave DFT calculations to generate reference data for MLIP fine-tuning.
• Develop materials property databases.
• Collaborate with computational scientists, AI researchers, and experimental teams to validate predictions.

Skills

Atomistic modelling

MLIP development

Python programming

High-throughput workflows

Education

PhD in Materials Science

PhD in Physics

Tools

VASP

Quantum ESPRESSO

Python tooling

Job description

A*STAR IAIC invites two new Research Scientists to advance AI-driven materials modelling and discovery. You will design MLIPs, run DFT workflows, and build scalable high-throughput pipelines to explore alloys, semiconductors, and thermal materials.

You will collaborate with computational scientists and AI researchers, publish in journals, and contribute to open-source software underpinning the workflow. Strong independence and teamwork are essential.