How can we navigate the digital age with confidence and integrity?

This programme, funded under the MOE AcRF T3 Grant, is an interdisciplinary research initiative that seeks to address the rising problem of mis-, dis-, and mal-information (MDM) in the complex terrain of our digital world. It recognizes the limitations of existing, mainly technical interventions, and adopts a comprehensive approach that emphasizes the role of consumer behaviour in the creation, dissemination, and consumption of digital information. Leveraging expertise from both computer science and social sciences, the programme aims to identify and mitigate vulnerabilities in the digital information pipeline, develop strategies to foster digital resilience among online users, and encourage behaviour towards trustworthy information.

The programme is structured into three main Research Spheres (RS):

• RS1 utilizes behavioral science to understand the motivations and decisions of consumers when they interact with digital information.

• RS2 encompasses of three Technology Domains (TD), each signifying different phases of the digital information pipeline:
  
  • TD1 employs machine learning techniques to detect and assess MDM across both text and visual content;
  • TD2 examines the influence of recommender systems and social media networks on shaping opinions and facilitating the formation of echo chambers;
  • TD3 uses natural language processing and information science to help consumers analyse information from diverse viewpoints.

• RS3 investigates interventions pertinent to policy and assesses how regulation and policies influence the supply and demand of digital information.

Our team of multidisciplinary researchers committed to understanding and shaping the digital information landscape.

Multiple research positions are open!

We have openings for motivated and skilled Research Fellows, Research Assistants and PhD students for our ambitious Digital Information Resilience Programme.

Responsibilities: Depending on your role, you will be expected to:

• Collaborate with a diverse team of computer scientists and social scientists to contribute to an interdisciplinary research programme.
• Conduct rigorous research and develop innovative solutions to complex problems.
• Publish and present research findings in academic journals and conferences.
• Assist in the development and testing of algorithms or behavioral models.
• Participate in regular team meetings and contribute to collaborative efforts.

Qualifications:

For Computer Scientists:

• A PhD (for Research Fellow position) or Bachelor/Master degree (for Research Assistant position) in Computer Science, Data Science, or related field.
• Proficiency in machine learning methodologies, natural language processing, and/or information science.
• Experience with programming languages such as Python, C/C++.
• Strong analytical and problem-solving skills.

For Social Scientists:

• A PhD (for Research Fellow position) or Bachelor/Master degree (for Research Assistant position) in Social Science, Psychology, Behavioral Economics, or related field.
• Proficiency in conducting behavioral studies and quantitative research methods.
• Understanding of digital consumer behavior and its societal implications.
• Excellent communication and writing skills.

For PhD Students:

• A Bachelor/Master degree in Computer Science, Social Science, Behavioral Economics, or related field.
• Have been offered admission to the NUS Graduate School.

Preferred Qualifications for all candidates:

• Prior experience in interdisciplinary research.
• Interest in the impact of digital technologies on society.
• Familiarity with issues related to misinformation, disinformation, and mal-information.

How to Apply: Please submit your CV, a brief statement of research interests and contact information for three referees to ctic@nus.edu.sg. Review of applications will begin immediately and continue until the positions are filled. Only shortlisted candidates will be contacted for an interview.