Senior Scientist / Scientist, Centre for Frontier AI Research, IAIC

A*STAR Research Entities (A*STAR); Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Publish opportunities

Collaboration with leading researchers

State-of-the-art compute resources

Interdisciplinary research environment

Job summary

A*STAR Research Entities (A*STAR) invites highly motivated research scientists to join the AI for Science team developing AI-driven approaches for material design and scientific discovery. The project aims to build foundation models and intelligent AI agents that accelerate design by integrating multimodal data, physics knowledge, and machine learning.

Successful candidates will work at the intersection of Artificial Intelligence and Materials Science, collaborating with leading academic and

Qualifications

• Background in Artificial Intelligence or Machine Learning
• Experience with deep learning and multimodal data
• Strong programming skills in Python and ML frameworks

Responsibilities

• Conduct cutting-edge research in AI for materials discovery and design
• Develop novel AI algorithms for inverse design and property prediction
• Collaborate with materials scientists to address real-world scientific challenges
• Design, implement, and evaluate AI systems using modern DL frameworks
• Publish research findings in leading AI and interdisciplinary venues

Job description

Job Summary

We are seeking highly motivated research scientists to join our AI for Science team developing next-generation AI-driven approaches for material design and scientific discovery. The project aims to build foundation models and intelligent AI agents that accelerate the design and understanding of advanced materials by integrating multimodal data, physics knowledge, and machine learning. Successful candidates will work at the intersection of Artificial Intelligence and Materials Science, contributing to cutting-edge research with opportunities to publish in top-tier AI and interdisciplinary venues, collaborate with leading academic and industry partners, and contribute to strategic national research projects.

Research Areas

Depending on your expertise and interests, you may contribute to one or more of the following areas:

• AI foundation models for materials and scientific data
• Multimodal learning integrating images, microstructures, text, simulations, and material properties
• Generative AI for inverse material design and optimization
• Scientific reasoning and AI agents for autonomous material discovery
• Diffusion models, large language models (LLMs), and multimodal large language models (MLLMs)
• Human-AI collaboration for scientific research

Responsibilities

• Conduct cutting-edge research in AI for materials discovery and design.
• Develop novel AI algorithms for inverse design, property prediction, and scientific reasoning.
• Collaborate with materials scientists and domain experts to solve real-world scientific challenges.
• Design, implement, and evaluate AI systems using modern deep learning frameworks.
• Publish research findings in leading AI and interdisciplinary conferences and journals.

Required Qualifications

Applicants should possess one or more of the following backgrounds:

• Artificial Intelligence
• Machine Learning
• Computer Science
• Data Science
• Computational Materials Science
• Mechanical Engineering
• Applied Mathematics
• Related disciplines

Candidates should have experience in some of the following:

• Deep learning (PyTorch or TensorFlow)
• Generative AI (Diffusion Models, VAEs, GANs, Transformers, LLMs)
• Representation learning
• Computer vision or multimodal learning
• Linux and GPU computing

Strong analytical, programming, and communication skills are expected.

What We Offer

• Opportunity to work on cutting-edge AI for Science research.
• Collaboration with leading researchers in artificial intelligence and materials science.
• Access to large-scale computing resources and state-of-the-art AI infrastructure.
• Opportunities to publish in top-tier conferences and journals.
• An interdisciplinary research environment with strong industry and academic collaborations.