The Advanced Remanufacturing and Technology Centre (ARTC) is seeking a Senior Research Scientist to advance AI-enabled solutions for manufacturing and industrial domains. The successful candidate will play a key role in development of advanced agetic intelligent systems that support decision-making, optimisation, and continuous improvement across diverse manufacturing scenarios.
You will collaborate with cross-functional teams to translate complex use cases into AI-ready representations, ensuring solutions are robust, explainable, and aligned with operational and regulatory requirements.
Key Responsibilities
Conduct research on agentic AI systems with a strong emphasis on reasoning and closed-loop evaluation.
Design and build advanced capabilities of intelligent agents to autonomously reason, justify, and evaluate decisions in complex, real-world environments.
Develop frameworks and methodologies for explainable, auditable, and policy-aligned explanations, ensuring solutions are robust and suitable for regulated industries.
Collaborate with cross-functional teams to integrate agent-based reasoning and evaluation into both R&D and industrial projects.
Contribute to the creation and sharing of reusable knowledge assets and frameworks that enhance collective intelligence and learning across agent networks.
Technical Requirement
PhD in Computer Science, Artificial Intelligence, Industrial Engineering, or a related field.
Significant experience in AI research, with a focus on agentic AI and reasoning systems in manufacturing and industrial domains.
Strong background in reasoning methods (e.g., symbolic, causal, temporal reasoning) and learning approaches (e.g., adaptive learning, meta-learning) for manufacturing knowledge and intelligence.
Proficiency in agentic AI frameworks and machine learning frameworks (e.g., PyTorch, TensorFlow, HuggingFace Transformers).
Familiarity with optimisation modelling, simulation logic, or rule-based systems.
Demonstrated ability to develop and deploy software solutions in both R&D and industrial project settings.
Excellent analytical, problem-solving, and communication skills.
Track record of publications in reputable conferences or journals.
Good to Have
Experience with explainable AI, privacy-preserving technologies, or federated learning.
Experience with knowledge representation (ontologies, knowledge graphs, semantic models).
Experience in regulated manufacturing or industrial AI applications.
The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.
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