About this role
Job Summary We are seeking a hands-on postdoctoral researcher at BEARS under AxCIS Project (AI xploration of Catalysis with Inorganics and Surfaces) in Singapore. This project uses AI and laboratory automation to develop integrated pathways for producing chemicals and fuels in a holistic approach to decarbonization. This role centers on integrating an LLM-driven agentic platform for electrocatalyst discovery and developing novel machine-learning algorithms (e.g., reinforcement learning) for materials discovery and process optimization. You will work closely with multidisciplinary team and architect and ship end-to-end, closed-loop workflows that connect instruments, edge devices, data backends, and AI agents. Duties & Responsibilities • Integrate instruments and IoT devices with reliable drivers/APIs; build autonomous/robotic testing workflows. • Design LLM agents for planning, tool-use, and experiment control with safety interlocks. • Develop and deploy RL/BO/active learning for closed-loop optimization. • Build data pipelines, dashboards, and provenance; analyse and present results. • Publish in peer review Journals and conferences, and coordinate with sponsors/collaborators. Qualifications • Ph.D. in Computer Science/ Electrical Engineering/ Robotics/ Chemical Engineering /Mechnical Engineering or related. • Strong in Python, with experience with hardware and software integration (serial/TCP/IP, MQTT, API). • Practical ML background, including RL/BO; Docker/Linux/Git familiarity. • Track record in automation or autonomous labs; good communication and collaboration skills.
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