Senior Scientist, Centre for Frontier AI Research, IAIC

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

Job Description

CFAR, A*STAR is looking for an innovative and experienced researcher to join its AI for Transdisciplinary Science (AI4TranS) Group. The candidate will play a leading research role in the AI for Science programme, with a focus on developing advanced AI methodologies and foundation models for scientific discovery. Research topics may include geometric and equivariant learning, graph learning, generative and foundation models, multi-fidelity learning, uncertainty-aware learning, agentic AI, and efficient AI, with applications to surface science, catalysis, materials, and related scientific domains. The candidate will work closely with AI researchers, domain scientists, and engineers to translate fundamental AI advances into scalable scientific discovery capabilities.

Successful candidates will be responsible, but not limited to:

1. Translate high-impact AI for Science research ideas into feasible research programmes and technical solutions.
2. Design and develop novel AI models for scientific discovery, including geometric/equivariant learning, graph and foundation models, generative modelling, and multi-fidelity learning
3. Develop rigorous evaluation frameworks and benchmark new methods on large-scale scientific datasets and real-world scientific problems
4. Lead research activities and supervise junior scientists, engineers, students, and research assistants to deliver high-quality research outcomes
5. Publish research outcomes in top-tier AI conferences and journals, and contribute to project milestones, collaborations, and technology translation

ABOUT A*STAR AND CFAR

At A*STAR, we make it our mission to attract and develop a diversity of talent along the research, innovation, and enterprise value chain, with career paths developed for scientists, engineers, and entrepreneurs. In return, we commit to investing in the personal and professional growth of each of our officers.

CFAR has a team of exemplary AI researchers committed to solving some of the most exciting problems in frontier AI, including IEEE fellows, chairs, scholars, and advisors among some of the most highly cited researchers in the world. Our AI Centre provides a unique research environment for fundamental AI research and cultivates next-gen AI scientists. If you share our interests in solving challenging engineering problems, we welcome you to apply.

JOB REQUIREMENTS

1. PhD degree in computer science, artificial intelligence, machine learning, applied mathematics, computational science, or other related fields
2. Strong research experience in one or more areas of AI, such as graph learning, geometric/equivariant learning, foundation models, generative AI, scientific machine learning, multi-modal learning, or efficient AI
3. Strong publication record in top-tier AI or related scientific computing venues, such as NeurIPS, ICML, ICLR, AAAI, IJCAI, KDD, AIJ, JMLR, TPAMI, NMI, or other high-quality journals and conferences
4. Strong problem-solving, analytical, and research leadership skills
5. Strong communication and presentation skills, with the ability to work effectively with both AI researchers and domain scientists
6. Ability to work independently, lead research tasks, supervise junior researchers, and collaborate across multidisciplinary teams