Postdoctoral Fellow - Governance of AI (Case Research, Online Experiments and Delphi)

Apply now »

Date: 14 Apr 2024

Location: LKYSPP, Bukit Timah Campus, SG

Company: National University of Singapore

Job Description

The Policy Systems Group at the Lee Kuan Yew School of Public Policy, National University of Singapore, is seeking applications for a full-time postdoctoral researcher position in Governance of AI (Case Research, Online Experiments & Delphi). The position is available immediately for 2 years.
The postdoctoral researcher will be hired to carry out the multidisciplinary research focused on Governance of AI under the PI’s supervision for 2 year. The research fellow is expected to have significant research experience in studying Governance of AI/Autonomous systems/Robotics in Public Policy or closely related fields.  The project using a policy design lens will contribute to the literature on governance of AI through mixed-method research in four phases that focus on trust in AI. In this postdoctoral appointment we will conceptualise trust in AI and identify factors to gauge public trust in AI that will serve as a foundation for examining factors such as trust in technology and trust in government to manage the risks. In this appointment the postdoctoral fellow will approach experts to identify essential factors and policy measures to ensure and maintain public trust in AI. Policy design involves choosing appropriate policy instruments, and to have more nuanced perspectives of these, expert surveys will provide insights on regulations for the safe operation of AI systems. We will conduct an online experiment involving respondents from Singapore to examine the institutions and regulatory arrangements that would enhance their trust in AI. The experiment will focus on high-risk AI applications in critical areas like surgery, public service provision, law enforcement, and justice. The findings from the work carried out by the postdoctoral fellow will be consolidated in the final phase of the project to suggest policy instruments to build and enhance trust in AI, particularly in Singapore.
A demonstrated research and publication in studying Governance of AI or Autonomous Systems or similar disruptive technologies is a must 

Qualifications

Applicants must have a relevant PhD before starting the position. The ideal applicant has a background and interest in multidisciplinary research in public policy AND AI/Autonomous systems/Robotics and has a strong publication track record. The applicant must have experience and aptitude for qualitative and quantitative research relevant to this multidisciplinary project particularly the in  case research, Surveys and quantitative analysis. Research experience and track record in conducting primary data collection and analysis in Asia is a plus. Strong applicants from social science disciplines, as well as interdisciplinary scholars trained and published in Public Policy AND AI Governance are encouraged to apply. 
Additional requirements
•    Excellent spoken and written English
•    The ability to follow instructions, adhere to deadlines and demonstrate attention to detail.
•    Ability to collaborate and work in a team, particularly with members of the policy systems group.

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Bukit Timah Campus

Organization: Lee Kuan Yew School of Public Policy

Department : Research Team

Employee Referral Eligible: No

Job requisition ID : 19094