Research Associate (AI & Policy)

NCPA’s core research areas are broadly categorised into 1) Global Asia, including Asian Models of Good Governance and ASEAN-China collaboration; 2) Public Policy and Emerging Technologies, with a particular focus on artificial intelligence (AI).

We are seeking to appoint two Research Associates: one in the area of Global Asia, and one in the area of AI and Policy. The appointments are for a period of two years.

The successful candidates will work closely with the Principal Investigator (PI) and Research Fellows at NCPA. They will contribute to research activities, provide operational and administrative support, and undertake project management responsibilities to ensure the timely and high-quality delivery of project outputs.

Key responsibilities:

• Conduct literature reviews, data collection and analysis, and synthesis of research findings; support the publication and dissemination of outputs in research reports, conference papers, academic journal articles, policy briefs, opinion editorials, and book manuscripts.

• Provide research and operational support for projects and activities, including but not limited to the Social Lab, conferences, seminars, and workshops.

• Maintain and manage research data in accordance with NTU’s Research Policies and Data Management Plans, ensuring compliance with institutional and funding requirements.

• Support project administration, including preparation of research reports, monitoring and management of research budgets, and coordination of travel arrangements (flights and accommodation) for the research team.

Job Requirements:

• Master's degree in public policy, public administration, management and economics, international political economy and any other relevant fields from a reputed university.

• Ability to work collaboratively with team members is particularly welcome.

• Strong background and demonstrated experience in research, field work, data collection and analysis, and publication.

• Familiarity with AI and its policy implications.

• Demonstrated quantitative and/or computational skills (e.g., large-scale data analysis, bibliometric analysis, machine learning methods) will be an advantage.

• Excellent written and oral communication skills.

We regret that only shortlisted candidates will be notified.