Senior Lecturer in Computational Social Science and Digital Literacy

Applications are invited for an appointment as Senior Lecturer in Computational Social Science and Digital Literacy (Ref.: 534005) in the Faculty of Social Sciences, to commence as soon as possible, on a two-year fixed-term basis, with the possibility of renewal subject to funding availability and satisfactory performance.

The Faculty of Social Sciences (FOSS) offers a wide range of undergraduate and taught postgraduate programmes that integrate quantitative, computational and social science approaches. The appointee will play a key role in advancing the Faculty's offerings in Computational Social Sciences (CSS), Master of Social Sciences in Social Data Analytics (MSDA) and Maser of Public Administration (MPA).

The appointee will contribute to teaching and curriculum development across undergraduate and postgraduate programmes, supervise graduate capstone projects, support programme operations (including admissions, recruitment, and digital promotion activities), advise students on their academic and professional development, and contribute to crossdisciplinary collaborations within the Faculty and the University.

Duties and Responsibilities

The appointee will teach and coordinate the following courses (or their equivalents):

Undergraduate (UG) Courses

1. FOSS - Introduction to Computational Social Science
2. SOCI - Programming for Social Scientists
3. AILT - Digital Literacy Through a Social Sciences Lens

Taught Postgraduate (TPg) Courses

1. MSDA - Statistical Foundations
2. MSDA - Causal Inference in the Social Sciences
3. SOCI - Quantitative Research Methods

Selection Criteria

Applicants should possess a Master's degree or above in Computational Social Science, Data Analytic Statistics, Sociology, Political Science, Public Policy or a relevant social science discipline with strong quantitative focus. Priority will be given to those with:

1. The ability to teach Machine Learning, Programming (Python-based), Natural language processing and Social Network Analysis courses on modern computational social science methods at the graduate level
2. A track record of completed projects working with computational models and large-scale social science data
3. Post-qualification working experience in relevant professional or academic settings
4. Interdisciplinary teaching and research and
5. Experience working with persons from diverse social, cultural and linguistic backgrounds is expected, alongside excellent communication skills in English.

What We Offer

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary.

How to Apply

The University only accepts online application for the above post. Applicants should apply online, and upload (1) a cover letter (2) an up-to-date CV and (3) a teaching statement. Review of applications will start as soon as possible and continue until January 9, 2026, or until the post is filled, whichever is earlier.