Tenured Full Professor in Computational Communication

Job Description

We are seeking Full Professor in Computational Communication, broadly envisioned as the application of computational techniques on various areas of communication and media studies. While our faculty within these areas are driving a wide variety of projects invoking state-of-the-art methods and tools, we envision the role of a Full Professor to define and steer the research directions towards meeting the larger vision and mission of the department to be Asia’s first and premier hub of computational social science research. The candidate would catalyse key intra-university collaborations with faculty in other departments to facilitate methodological innovations, as well as inter-university connections that widen the impact of the computational communication research at NUS in the broader regional and international area.

The ideal candidates must be well-versed with state-of-the-art computational research, methods and techniques, evidenced through publications that break new ground, and international recognition and leadership roles. The candidate would enrich the research culture at CNM through building the research agenda and obtaining large research grants, influence key decisions through service roles involving administration, hiring, collaborations, and outreach, and mentor future generations of scholars through teaching and advisory roles. 

While their disciplinary training may vary, ideal candidates would show evidence of leadership, international renown, and an established reputation in the research community in one or more of the following areas: computational social science, media and communication studies, information sciences, and computer science.  
 

Qualifications

Interested applicants must have a PhD in Communication or related discipline, with evidence of leadership in pioneering innovative methodologies and theories, applying computational social science methods to resolve complex communication and media questions; as well as evidence of excellence in teaching. Candidates should demonstrate ability to use computational methods such as machine learning, multimodal analysis, natural language processing, network analysis, and online experiments in applied contexts such as sustainability, wellbeing, social movements, and public opinion. Candidates must have experience with computational techniques using R or Python and the ability to teach courses in computational communication, social media research, multimodal analysis, network analysis, and/or time series analysis.

Application Instructions (30 Jun 2025)

Interested applicants are required to submit a complete application dossier as listed below for full consideration. Only shortlisted candidates will be notified.

1. Cover Letter
2. Full curriculum vitae detailing your academic history, i.e. degrees obtain, scholarships and awards, postdoctoral training, employment history (academic and non-academic positions), all PhD and postdoctoral supervisors or any other senior authors with close and regular collaborations (full name and institution) should be listed, grants, invited talks, research activities and achievements. 
3. Teaching Statement of teaching philosophy and methodology (max 3 pages). Where available, evidence of teaching ability such as student feedback or peer review reports should be provided. Evidence of other contributions to education, such as curriculum development, pedagogical innovation, production of teaching materials, should be provided were available. 
4. Research Statement of major accomplishments in research (max 3 pages), citing up to 5 significant publications, creative work, or other scholarly contribution, and explaining their significance. 
5. Five (5) key publications should be provided (in the case of books, reviews should be provided). 
6. A research plan (max 3 pages) with a proposed start-up research budget and utilisation plan. 
7. Diversity Statement (max 3 pages)
8. A complete list of publications, grouped according to papers, books, and reviews, including page numbers, in bibliographic form.
9. Citation (excluding self-citations and in the case of co-authored work, cross-citations) and impact analysis of research output, highlighting papers with the highest citation counts, and creative works with high impact.
10. Documents on service contributions (max 3 page). List and elaborate on the impact of service to department/faculty/university, international academic community, and/or national and international agencies. 
11. A list of SIX external reviewers recommended (names, contact details, applicant's relationship to them). These external reviewers should preferably not be close collaborators or the applicant's PhD/post-doc supervisor.
     

For more information on NUS please visit: www.nus.edu.sg. For more information about the Department of Communications and New Media, please visit https://fass.nus.edu.sg/cnm/.

Please note that only shortlisted candidates will be contacted.

More Information

Location: Kent Ridge Campus

Organization: Arts & Social Sciences

Department : Communications And New Media

Employee Referral Eligible: No

Job requisition ID : 26628