Research Fellow (Laboratory for Advanced Materials Synthesis)

Job Title: Research Fellow (Laboratory for Advanced Materials Synthesis)

University-Level Unit: Institute for Functional Intelligent Materials

Faculty/Department-Level Unit: Research Groups

Employee Category: Research Staff

Location_ONB: Kent Ridge Campus

Posting Start Date: 30/09/2026

Job Description

The Institute for Functional Intelligent Materials (I-FIM) at the National University of Singapore is establishing a new state-of-the-art material robotics laboratory dedicated to the advanced synthesis and testing of functional materials, AI-driven autonomous experimental design, and robotic automation. We are seeking a highly motivated materials expert to (1) lead the strategic development and day-to-day operations of the material robotics laboratory, and (2) oversee the operation and management of an established furnace cluster. Experience in the synthesis of low-dimensional materials and thin films using high-temperature growth techniques is highly preferred. This role offers a unique opportunity to shape a cutting-edge facility at the forefront of materials discovery and to work closely with interdisciplinary teams spanning computation, automation, and synthesis.

Key Responsibilities

• Key equipment to manage: A fully automated metal-organic chemical vapor deposition (MOCVD) platform, integrated with in-situ testing equipment and supported by gas-handling systems, scrubbers, and a glovebox for safe handling of air-sensitive chemicals and precursors in the material robotics laboratory. Multiple furnaces (tube, muffle), ovens and reactors in the furnace cluster.
• Strategic Leadership & Vision - Support the development and execution of a research roadmap for AI-guided autonomous synthesis of novel functional materials using CVD and high temperature material synthesis platforms
• Laboratory Setup & Management - Oversee the commissioning of furnaces, robotic platforms, and digital infrastructure for synthesis automation. Develop standard operating procedures (SOPs), safety protocols, and maintenance schedules.
• Safety & Compliance - Develop RAs, SOPs, and safety procedures; manage chemical, gas, high-temperature, vacuum, and equipment hazards; ensure EHS compliance; conduct inspections, training, and corrective actions.
• Equipment Management & Reliability - Manage the equipment lifecycle from procurement and commissioning through maintenance and decommissioning; coordinate FAT/SAT, qualification, calibration, servicing, and troubleshooting
• Technical & Engineering Support - Troubleshoot equipment and process issues; work with researchers, engineers, and OEMs; develop custom solutions and drive equipment/process improvements
• Procurement & Vendor Management - Develop technical specifications, evaluate proposals, manage procurement and acceptance, coordinate vendors, and support equipment and maintenance budgets
• Collaboration & Supervision - Collaborate with researchers across synthesis, computation, automation, and characterization to implement closed-loop materials discovery workflows
• AI Integration - After validating manual experiments, work closely with the institute's AI team to integrate machine learning and autonomous decision-making into the synthesis workflow. Assist in developing or utilizing active learning strategies to optimize synthesis conditions
  
  

Job Requirements

• PhD in Materials Science, Chemistry, Physics, or related field
• Requirement of a PhD might be waived off if the candidate comes with substantial relevant industry experience
• Strong track record in solid-state or thermal synthesis techniques (e.g., CVD, tube furnace synthesis, rapid thermal annealing, ampule synthesis, self-flux, CVT, etc)
• Experience in establishing new lab infrastructure or managing complex research projects
• Proven ability to manage a research group or laboratory setting
• Excellent communication and collaborative skills
• Bonus to have familiarity with lab automation, robotic platforms, or in-situ diagnostics is highly desirable
• Bonus to have demonstrated experience with AI/ML integration in materials science or a strong interest in learning and applying these tools
  
  

Req ID: 34552