Job Summary
The Centre for Frontier AI Research (CFAR), IAIC, A*STAR is seeking a Research Scientist in Agentic AI to develop algorithms and systems for open-domain, long-horizon agentic AI. The role focuses on building and optimising agentic systems that can formulate plans, use tools and models, coordinate across agents, and improve through execution, feedback, and interaction with complex environments. The research will bring together planning, search, learning, memory, multimodal grounding, and neural-symbolic composition to create agents that are capable, reusable, and reliable beyond narrowly specified tasks.
The successful candidate will translate this research capability into reusable frameworks, benchmarks, open-source systems, and prototypes that strengthen CFAR’s long-term research portfolio. The role involves publishing high-quality research, contributing to national AI research programmes and competitive grant proposals, and maturing agentic AI methods for complex real-world settings, including digital services, scientific R&D, healthcare, governance, and enterprise operations.
Job Scope
The successful candidate will:
- Conduct frontier research on agentic AI systems for open-domain and long-horizon problems, with emphasis on planning, search, learning, tool use, memory, multimodal grounding, multi-agent coordination, and self-improvement from execution.
- Develop reusable agentic AI frameworks and algorithms for building, optimising, evaluating, and improving agents across tasks, domains, and partner settings.
- Produce high-impact research outputs, including publications at leading AI venues, open-source code, benchmarks, evaluation protocols, datasets, and reusable system components.
- Contribute to national AI research programmes, competitive grant proposals, and strategic research initiatives in areas related to agentic AI and foundation model systems.
- Mature research prototypes into deployable agentic AI technologies for complex real-world problems in digital services, scientific R&D, healthcare, governance, and enterprise operations.
- Mentor junior researchers, research engineers, interns, and students, and contribute to the development of CFAR’s long-term research agenda in agentic AI.
Job Requirements
Candidates should have:
- A PhD in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field.
- A strong publication record at leading AI venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, AAAI, IJCAI, or IEEE TPAMI.
- Deep expertise in agentic AI and at least one related area, such as LLM agents, multi-agent systems, multimodal reasoning, reinforcement learning, planning and search, program synthesis, neural-symbolic AI, tool-use learning, or autonomous decision-making.
- Strong programming ability in Python and modern machine learning frameworks such as PyTorch or JAX, with experience building research prototypes or end-to-end AI systems.
- Evidence of research impact beyond individual publications, such as open-source software, reusable benchmarks, cited datasets, shared infrastructure, deployed prototypes, or research artefacts adopted by others.
- Strong communication and collaboration skills, with the ability to contribute to grant proposals, work across multidisciplinary teams, and engage effectively with research, agency, and industry partners.