Lead AI Scientist for Scientific Discovery & Graph Models

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

Job summary

CFAR, A*STAR invites an innovative researcher to lead AI for Transdisciplinary Science initiatives. You will design advanced AI models, including graph and foundation models, for scientific discovery and multi-fidelity learning.

You will work with AI researchers, domain scientists, and engineers to translate fundamental AI advances into scalable discovery capabilities. The role focuses on shaping research programmes, mentoring junior staff, and publishing results in premier AI conferences and

Qualifications

• PhD in computer science, artificial intelligence, machine learning, or related fields.
• Strong research experience in AI areas such as graph learning, geometric/equivariant learning, foundation models, generative AI, or scientific ML.
• Strong publication record in top AI or related venues.
• Strong problem-solving, analytical, and leadership skills.
• Excellent communication and ability to work with researchers and domain scientists.
• Ability to lead independent research tasks and collaborate across teams.

Responsibilities

• Translate research ideas into feasible programmes and solutions.
• Design novel AI models for scientific discovery and complex data.
• Develop evaluation frameworks and benchmark methods on large datasets.
• Lead research activities and supervise junior researchers and staff.
• Publish results in top AI conferences and journals and track progress.

Skills

Research leadership

Publications

Communication skills

Independent work

Team collaboration

Education

PhD in CS/AI/ML

Tools

Python

PyTorch

Job description

CFAR, A*STAR invites an innovative researcher to lead AI for Transdisciplinary Science initiatives. You will design advanced AI models, including graph and foundation models, for scientific discovery and multi-fidelity learning.

You will work with AI researchers, domain scientists, and engineers to translate fundamental AI advances into scalable discovery capabilities. The role focuses on shaping research programmes, mentoring junior staff, and publishing results in premier AI conferences and