Postdoctoral Fellow in Computational Social Science
Candidates will have expertise in one or more of the following areas: statistical modelling; big data analytics; machine learning; natural language processing; network science; survey/experimental methods; causal inference; econometrics.
PhD in a discipline closely related to computational social science by date of appointment, with evidence of interdisciplinary research applying computational methods to the social sciences. This includes but is not limited to social science disciplines (sociology, political science, communication, economics etc.) or computer science and related disciplines (information science, data science, computational physics etc.)
Evidence of successful teaching in methods or theory.
This is a full-time position for 2 years. The incumbent is expected to teach 2 modules related to computational methods per year (50%) and work with existing faculty members in pursuing computational social science research projects (50%). The incumbent will also contribute towards publishing top-tier journal articles and curriculum development in computational communication. The incumbent should expect to work with multiple projects and faculty advisors. The anticipated start date is 1 January 2023 prior to the beginning of the semester in January 2023.
Interested applicants are required to submit a complete application dossier as listed below for full consideration.
Only shortlisted candidates will be notified.
- NUS Personal Data Consent Form for Job Applicants (You may download the file via this link http://www.nus.edu.sg/careers/files/NUS-Personal-Data-Consent-for-Job-Applicants.pdf).
- Full CV: academic and employment history, degrees obtained, scholarships and awards, post-doctoral and clinical/ residency training (where applicable), other study and research opportunities, Name of PhD supervisor, etc.
- Scanned copies of academic certificates and transcripts
- Documents relating to research
- A statement (max of 3 pages) of major accomplishments in research, citing up to five research, citing up to five significant publications, creative work or other scholarly contribution, and explaining their significance.
- Sample copies of these contributions should be provided (in the case of books, reviews should be provided).
- A complete list of publications
- Evidence of impact, e.g. citations (excluding self-citations)
- Evidence of international visibility, e.g. invitations to speak, major keynotes and plenary addresses, elected membership in professional and learned societies, membership on editorial boards of leading journals.
- Research awards
- Documents relating to service activities and impact
- At Department/Faculty/University levels
- To the international academic community
- To national and international agencies
- Documents relating to education (including the supervision of junior researchers), if applicable
- Teaching Portfolio
- A preface (maximum 300 words) that makes the case for your appointment. This should be highly distilled summary of your key contributions to student learning and educational leadership, guided by your teaching philosophy.
- A Teaching Statement that focuses on evidence of student learning and educational leadership (if applicable). Note that the Teaching Statement, together with documents on research (where applicable) and service contributions should be 3-5 pages. Examples of consideration that can guide the candidate in making a case for teaching impact and leadership, with a focus on self, students, others, scholarship, future plans.
- Samples of teaching evaluation reports (including the highest and lowest scores achieved)
- Diversity Statement
- A list of FOUR Referees (including one from the applicant’s PhD or post-doctoral advisor/supervisor). Referees are to submit their letters directly to email@example.com.
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.
Location: Kent Ridge Campus
Organization: Arts & Social Sciences
Department: Communications And New Media
Employee Referral Eligible: No
Job requisition ID: 16485