Research Fellow, AI & Technology Risk

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow%2C-AI-&-Technology-Risk/33693-en_GB/ We regret that only shortlisted candidates will be notified. Job Description The Research Fellow will be a member of the IPUR research team, working under the Director to help deliver IPUR’s research programme on risk perceptions and communications in the field of artificial intelligence (AI) and technology. Specifically, the RF will focus on designing, managing, and implementing quantitative and qualitative research on public perceptions and behavioural responses to AI and technology risk in Singapore and internationally, in addition to providing support in project and grant management, stakeholder liaison and outreach for IPUR. Responsibilities will include contributing to literature review, field research design and implementation, qualitative and quantitative data analysis, organisation of seminars and events, preparing scholarly publications and preparation of outreach materials. Candidates should have a background in economics, statistics, psychology, or information technology, and have an interest in and awareness of AI and technological issues. All candidates should have a strong willingness to learn about new topics and methods. Applicants with experience in quantitative research methods will be given preference. Reponsibilities Collect and manage primary and/or secondary data for research projects Perform quantitative/qualitative data analysis Write literature reviews, research briefings and summaries Assist in fieldwork and serve as liaison for field researchers Preparation of grant proposals and institute reporting requirements for stakeholders Provide support for IPUR events and outreach activities This is a 1-year, onsite position in Singapore. Requirements PhD in economics, statistics, psychology, information technology, or other relevant discipline (work experience in applied research preferred) Strong quantitative analytical skills (experience in survey/experimental design and analysis in STATA/R preferred) Good organisational skills Excellent spoken and written English Application Procedure Please include the following documents in the application: A cover letter (max. 1 page), with a brief statement of relevant expertise Curriculum vitae including a list of academic publications Details of two referees, including at least one academic referee, who can comment on the applicant’s abilities and experience