Assistant Manager / Senior Executive – Lab Operations

About the role

NTU’s College of Computing and Data Science is seeking an Assistant Manager / Senior Executive to lead laboratory operations. The role supports graduate research labs and centralised research computing facilities, ensuring they run smoothly and safely.

Key responsibilities

• Support operations, infrastructure and technical environments of CCDS graduate research laboratories and centralised research computing facilities, including GPU, server and specialised research equipment.
• Ensure operational readiness, reliability and effective functioning of laboratory and research computing infrastructure, covering configuration, deployment, maintenance and troubleshooting of workstations, servers and GPU‑enabled systems.
• Coordinate procurement, vendor management and asset lifecycle activities to keep research infrastructure and equipment available for faculty, researchers and students.
• Administer laboratory access, safety, compliance and audit requirements, aligning with relevant policies and standards.
• Collaborate with faculty, researchers, students and other stakeholders to continuously improve efficiency and effectiveness of research laboratory and computing operations.
• Leverage Generative AI and AI‑enabled tools to enhance information analysis, technical documentation, workflow automation, troubleshooting and operational productivity.

Required profile

• Bachelor’s degree or Diploma in IT, Computer Science, Data Science, AI, Engineering or a related discipline.
• Relevant professional certifications in AI, Generative AI, Machine Learning, Data Analytics, Cloud Computing or IT Infrastructure are advantageous.
• Experience in technical support, infrastructure administration, laboratory operations or research computing environments.
• Strong organisational, troubleshooting, analytical, communication and stakeholder‑management skills.
• Ability to work independently and collaboratively in a dynamic, technology‑driven research environment.

Required skills

• Linux operating system.
• Scripting or programming knowledge such as Python, Bash or PowerShell.
• Servers, GPU‑enabled systems and workstations.
• Virtualisation and cloud platforms.
• Scientific computing and AI/ML research infrastructure.
• Generative AI and modern AI productivity tools.