Senior Scientist, AI-Driven Materials Modelling

A*STAR RESEARCH ENTITIES

Singapore

On-site

SGD 120,000 - 180,000

Full time

2 days ago

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Job summary

A*STAR Institute of Advanced Intelligence and Computing (IAIC) in Singapore invites applications for two Research Scientist positions focusing on AI-driven materials modelling and discovery. You will develop foundation potentials, train MLIPs, and design high-throughput screening workflows for thermal properties of alloys and semiconductors.

Applicants should hold a Ph.D. and demonstrate strong expertise in atomistic modelling, DFT, MLIPs, and HPC.

Qualifications

Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Mechanical Engineering, 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 established electronic structure packages (e.g. VASP, Quantum ESPRESSO).
Hands-on experience developing, training, fine-tuning, and applying MLIPs or other atomistic machine learning models (e.g. M3GNet, TensorNet, MACE, GRACE, etc.).
Experience with molecular dynamics and lattice-dynamics methods for thermal and mechanical property prediction, such as Green-Kubo or non-equilibrium MD, phonon Boltzmann transport, and quasi-harmonic approximations.
Experience in high-throughput materials workflow automation, including automated error handling and provenance tracking.

Responsibilities

Develop and apply foundation potentials and fine-tuned MLIPs to predict phase stability, lattice and electronic thermal conductivity, thermal expansion, and elastic properties at scale.
Design and execute high-throughput screening workflows on thermal expansion, thermal conductivity, and stability, among other properties.
Perform plane-wave DFT calculations to generate reference potential-energy-surface and property data for MLIP fine-tuning and validation.
Develop materials property databases.
Collaborate closely with computational scientists, AI researchers, and the experimental teams to validate predictions, interpret characterisation data, and generate new hypotheses.
Engage with industry partners and relevant stakeholders, including co-authoring industry-facing technical briefs.
Publish research findings in leading international journals, present at major scientific conferences, and contribute to software underpinning the workflow.